Determining antigen-specific t-cells

ABSTRACT

The invention is directed to methods for determining antigen-specific T cells. In some embodiments, methods of the invention may be implemented by the steps of reacting under interaction conditions one or more antigens with T cells in a plurality of subsets of a tissue sample, such as peripheral blood; sorting antigen-interacting T cells from other T cells; separately sequencing for each subset recombined nucleic acid encoding a segment of a TCR chain from a sample of T cells prior to exposure to antigen and from a sample of T cells isolated based on their interaction with antigen, thereby forming a clonotype profile for the former sample and the latter sample for each subset; and identifying as antigen-specific T cells those T cells associated with a clonotype whose frequency increases in the latter sample relative to its frequency in the former sample.

BACKGROUND OF THE INVENTION

Many crucial immune functions are mediated by T cell receptors (TCRs),which comprise α and β subunits that together bind to a complexconsisting of an antigenic peptide and major histocompatibility complex(MHC) molecules. It is believed that several important diseases arisefrom aberrant T cell function. For example, cancers are thought to arisefrom a failure of immune surveillance, that is, the T cell function ofdetecting and destroying clones of transformed cells before they growinto tumors; and autoimmune diseases are thought to arise from an overactive or aberrant response of T cells to self antigens, Abbas et at,Cellular and Molecular Immunology, Fourth Edition (W.B. SaundersCompany, 2000). Consequently, there has been interest both inidentifying and tracking antigen-specific T cells and in harnessing Tcell functions in several therapeutic approaches for the treatment bothcancer and autoimmune diseases. e.g. Molloy et al, Current Opinion inPharmacology, 5:438-443 (2005); Morgan et al, Science, 314: 126-129(2006); Turcotte and Rosenberg, Adv. Surg., 45: 341-360 (2011). Severalchallenges are posed by these interests: Current techniques foridentifying and tracking antigen-specific T cells, especially on a largescale, are difficult and expensive, and likewise, current techniques foridentifying and isolating paired TCRα and TCRβ subunits that form afunctional receptor are difficult and expensive. In regard to detectingantigen-specific T cells, the use of direct multimer staining requireslaborious development of specific HLA-restricted reagents, and otherassays, such as ELISPOT, intracellular cytokine staining, andproliferation assays, enumerate antigen-specific T cells based ondetection of activation following stimulation of the T cells in vitrowith antigen, e.g. Gratama et al, Cytometry A, 73A: 971-974 (2008). Inregard to isolating functional pairs of TCR chains, typically a T cellof interest is identified and clonally expanded to enable isolation andanalysis of nucleic acids encoding each subunit. Even for a commondisease antigen, such as MART-1 in melanoma, the process of single cellanalysis, cloning and receptor isolation must be repeated for eachpatient.

Recently, diagnostic and prognostic applications have been proposed thatuse large-scale DNA sequencing as the per-base cost of DNA sequencinghas dropped and sequencing techniques have become more convenient, e.g.Welch et al. Hematology Am. Soc. Hematol. Educ. Program, 2011: 30-35;Cronin e al, Biomark Med., 5: 293-305 (2011); Palomaki et al. Geneticsin Medicine (online publication 2 Feb. 2012). In particular, profiles ofnucleic acids encoding immune molecules, such as T cell or B cellreceptors, or their components, contain a wealth of information on thestate of health or disease of an organism, so that diagnostic andprognostic indicators based on the use of such profiles are beingdeveloped for a wide variety of conditions. Faham and Willis, U.S.patent publication 2010/0151471; Freeman et al, Genome Research, 19:1817-1824 (2009); Boyd et al. Sci. Transl. Med., 1(12): 12ra23 (2009);He et al, Oncotarget (Mar. 8, 2011). Current sequence-based profiles ofimmune repertoires consist of nucleic acids encoding only singlereceptor chains; thus, potentially useful information from correctlypaired TCRα and TCRβ chains chains is not available.

In view of the above, it would be highly useful for cancer, infectiousdisease and autoimmune disease treatment if there were availableconvenient methods for determining functional immune receptors fromnucleic acids encoding subunits that have been separately extracted andsequenced.

SUMMARY OF THE INVENTION

The present invention is drawn to methods for determining T cellreceptors from subunits selected from separate libraries, particularlyantigen-specific T cell receptors. The invention is exemplified in anumber of implementations and applications, some of which are summarizedbelow and throughout the specification.

In one aspect, the invention includes methods for determiningantigen-specific T cells in a tissue sample comprise steps of (a)reacting under activation conditions in a reaction mixture a tissuesample comprising T cells to an antigen; (b) sorting T cells from thereaction mixture into a subset of antigen-specific T cells and/oractivated T cells and a subset of non-antigen-specific T cells and/orunactivated T cells; (c) sequencing recombined nucleic acids encoding aT-cell receptor chain or a portion thereof from a sample of T cells fromthe antigen-specific T cells and/or activated T cells to providesequence reads from which clonotypes are determined; (d) sequencingrecombined nucleic acids encoding a T-cell receptor chain or a portionthereof from a sample of T cells from the non-antigen-specific T cellsand/or unactivated T cells to provide sequence reads from whichclonotypes are determined; and (c) determining antigen-specific T cellsin the tissue sample as T cells whose clonotype frequencies increase inthe subset of sorted antigen-specific and/or activated T cells relativeto the frequencies of the same clonotypes in the reaction mixture or thesubset of sorted non-antigen-specific and/or unactivated T cells.

In another aspect, the invention includes methods of determiningreceptors of antigen-specific T cells in a tissue sample comprising thefollowing steps: (a) forming a plurality of subsets from a tissue samplecontaining T cells; (b) reacting under activation conditions the T cellsof each subset to an antigen; (c) isolating the antigen-specific T cellsof each subset; (d) sequencing recombined nucleic acids encoding T-cellreceptor α chains in each subset to provide sequence reads from which αchain clonotypes are determined; (c) sequencing recombined nucleic acidsencoding T-cell receptor β chains in each subset to provide sequencereads from which β chain clonotypes are determined; and (f) identifyingas antigen-specific T cell receptors with those pairs of α chainclonotypes and β chain clonotypes that for every subset (i) either boththe α chain clonotype and β chain clonotype are present in a subset orneither are present in a subset, and (ii) both the α chain clonotype andβ chain clonotype are present in at least one subset and the α chainclonotype and β chain clonotype are not present in at least one subset.

These above-characterized aspects, as well as other aspects, of thepresent invention are exemplified in a number of illustratedimplementations and applications, some of which are shown in the figuresand characterized in the claims section that follows. However, the abovesummary is not intended to describe each illustrated embodiment or everyimplementation of the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

The novel features of the invention are set forth with particularity inthe appended claims. A better understanding of the features andadvantages of the present invention is obtained by reference to thefollowing detailed description that sets forth illustrative embodiments,in which the principles of the invention are utilized, and theaccompanying drawings of which:

FIG. 1A illustrates diagrammatically steps of one embodiment of theinvention for matching TCRα and TCRβ chains from separately sequencedmolecules.

FIG. 1B illustrates diagrammatically steps of another embodiment of theinvention for determining either TCRα and TCRβ chains that originatefrom the same T cell or heavy and light chain immunoglobulins thatoriginate from the same B cell.

FIG. 1C illustrates diagrammatically an embodiment of the invention foridentifying antigen-specific T cells that interact with a singleantigen.

FIG. 1D illustrates diagrammatically an embodiment of the invention foridentifying antigen-specific T cells that interact with a plurality ofantigens.

FIG. 1E illustrates steps of an embodiment of the invention for physicalidentification of antigen-specific T cells using single cellmethodology.

FIG. 1F illustrates a PCA scheme for linking target sequences wherepairs of internal primers have complementary.

FIGS. 2A-2C show a two-staged PCR scheme for amplifying TCRβ genes.

FIG. 3A illustrates details of determining a nucleotide sequence of thePCR product of FIG. 2C. FIG. 3B illustrates details of anotherembodiment of determining a nucleotide sequence of the PCR product ofFIG. 2C.

FIG. 4 illustrates an example of a tissue sample divided or aliquotedinto a plurality of subsets 1 through 10 and examples of differentsubpluralities of subsets of the plurality.

FIGS. 5A and 5B illustrate an embodiment of the invention fordetermining T-cells and TCRs specific for a plurality of antigens.

FIG. 6 shows data for identification of CMV pp65₁₉₅-specific T cellclonotypes from sorted pentamer+ T cells. Panel (A) shows clonotypefrequencies from CMV pp65495 pentamer+ versus pentamer− CD8+ T cellsfrom a characterized CMV responder. The 8 dots (enclosed in dashedelipse 600) indicate clonotypes greater than 10-fold enriched andexceeding a 20-cell equivalent minimum frequency threshold in the sorted(pentamer+) population, (B) All 8 clonotypes identified in panel A areenriched in (unsorted) PBMCs from the same individual. The dots enclosedby the dashed elipse (602) indicate clonotypes identified in panel A.

FIG. 7 shows data for identification of CMV pp65₄₉₅-specific T cellclonotypes from sorted responding cells following peptide incubation.Clonotype frequencies from sorted responding CD37+ cells following CMVpp65₄₉₅ peptide incubation versus either sorted non-responding CD137−cells (panel A) or unsorted PBMCs (panel B). The 9 data points enclosedby dashed elipse (700) in panel A indicate clonotypes greater than10-fold enriched and exceeding a 20-cell equivalent minimum frequencythreshold in the sorted (CD137+) population. Data points enclosed indashed elipse (702) in panel B indicate those clonotypes identified inpanel A. Clonotypes identified in panel A are not enriched in sortedCD137+ cells versus CD137− T cells (panel C arrows indicating datapoints corresponding to those enclosed by elipes in panels A and B)following incubation without peptide.

FIG. 8 illustrates the overlap between clonotypes identified inpentamer-based and CD137-based assays. In panel A, the plot showsclonotype frequencies of the 8 clonotypes (enclosed by dashed elipse800) identified in the pentamer analyses in the clonotype profiles ofCD137+ responding cells following CMV pp65₄₉₅ peptide incubation versussorted non-responding CD137-cells. In panel B, the plot shows clonotypefrequencies of the 9 clonotypes (enclosed by dashed elipse 802)identified in the CD137 assay analyses in the clonotype profiles ofsorted CMV pp65₄₉₅ pentamer+ cells versus pentamer− cells—8/9 of theseclonotypes are overlapping with those identified in panel A.

FIG. 9 shows data for identification of low-frequency CMVpp65495-specific T cell clonotypes following peptide incubation andproliferation. In panel A, clonotype frequencies from sortedproliferating CD8+ T cells following CMV pp65₄₉₅ peptide incubation atday 6 versus fresh unsorted PBMCs. The 16 data points (enclosed bydashed elipse 900) indicate clonotypes greater than 10-fold enriched andexceeding 1/10,000 minimum frequency threshold in the sortedproliferating cells. Panel B shows data of clonotype frequencies fromsorted proliferating CD8+ T cells following incubation without peptideat day 6 versus fresh unsorted PBMCs. Clonotypes (represented by datapoints enclosed by dashed elipses (902) are those identified in A. PanelC shows data of clonotype frequencies from CMV pp65495 pentamer+ versuspentamer− CD8+ T cells. Dashed elipses (904) and arrow (906) indicatethe 16 clonotypes identified in the proliferation assay whose resultsare represented in panel A with those clonotypes identified in the CMVpp65₄₉₅ pentamer+ versus pentamer− CD8+ T cell comparison. Panel D showsdata of clonotype frequencies from CMV pp65₄₉₅ pentamer+ versuspentamer− CDK+ cells. Data points enclosed by dashed elipses (908) anddesignated by arrows (910) indicate the 25 clonotypes identified in avariant of the proliferation assay described above with those clonotypesidentified in the CMV pp65₄₉₅ pentamer+ versus pentamer− CD8-4 T cellcomparison. In this assay a pool of 138 overlapping peptides from pp65was used instead of the single pp65₄₉₅ peptide.

DETAILED DESCRIPTION OF THE INVENTION

The practice of the present invention may employ, unless otherwiseindicated, conventional techniques and descriptions of molecular biology(including recombinant techniques), bioinformatics, cell biology, andbiochemistry, which are within the skill of the art. Such conventionaltechniques include, but are not limited to, sampling and analysis ofblood cells, nucleic acid sequencing and analysis, and the like.Specific illustrations of suitable techniques can be had by reference tothe example herein below. However, other equivalent conventionalprocedures can, of course, also be used. Such conventional techniquesand descriptions can be found in standard laboratory manuals.

Identifying Paired T-Cell Receptor Chains Without Antigen-SpecificSelection

In one aspect, the invention provides methods for matching pairs ofimmune receptor chains from populations of their encoding nucleic acidsthat have been sequenced. In accordance with one embodiment of theinvention, nucleic acid populations encoding repertoires of heavy chainvariable regions and light chain variable regions are sequenced so thattwo separate lists of sequences are formed without any correspondencebetween members of each list. This may be achieved by carrying outseparate sequencing operations, or runs, for each chain, or it may beaccomplished by carrying out a single sequence run with the nucleicacids tagged according to the identity of the type of chain it encodes.In accordance with another embodiment of the invention, nucleic acidpopulations encoding repertoires of T cell receptor alpha (TCRα) chainsand T cell receptor beta (TCRβ) chains are sequenced, so that twoseparate lists of sequences are formed without any correspondencebetween members of each list. In accordance with another embodiment ofthe invention, nucleic acid populations encoding repertoires of T cellreceptor gamma (TCRγ) chains and T cell receptor delta (TCRδ) chains aresequenced, so that two separate lists of sequences are formed withoutany correspondence between members of each list. As above, this may beachieved by carrying out separate sequencing runs for each chain, or itmay be accomplished by carrying out a single sequence run with thenucleic acids tagged according to the identity of the type of chain itencodes (that is, either TCRα and TCRβ, or TCRγ and TCRδ, respectively).In the latter embodiments, two approaches may be followed for matchingor pairing TCRα and TCRβ (or TCRγ and TCRδ) chains into chains that arefunctional, for example, because they originate from the same T cell. Ina first approach, the frequencies of each encoding nucleic acid aredetermined and TCRα chains and TCRβ chains whose encoding nucleotidesequences have the same frequencies are paired to form a functional, orreconstituted, TCR. TCRγ and TCRδ chains may be matched by the sameprocess. In a second approach, which is applicable to matching all threetypes of immune receptor pairs, a lymphocyte population is repeatedlydivided into a plurality of subsets. Such subsets may be obtained byaliquoting a tissue sample into separate reaction vessels or chambers.Separately from each of a portion, or subpopulation, of the subsets,nucleic acids encoding the two different immune receptor chains areextracted and sequenced, so that two separate lists of sequences areformed without any correspondence between members of each list. Asdescribed above, this may be achieved by carrying out separatesequencing runs for each chain, or it may be accomplished by carryingout a single sequence run with the nucleic acids tagged according to theidentity of the type of chain it encodes. To illustrate by an example,if a sample containing T cells or B cells is aliquotted into 100sub-samples, so that on average each aliquot contains a subsetconsisting of about 1/100 of the total number of T cells or B cells inthe original sample, then 20 such subsets may be randomly selected as aportion of the total number of subsets. (Such portion could be anynumber greater than one and less than 100, although as described morefully below, a number in the range of from 10 to 20 is a good trade offbetween amount of sequencing required and likelihood of identifyingreceptor pairs present at a frequency of interest). In one embodiment, aplurality of subsets is in the range of from 20 to 2000 and a portion ofsubsets thereof is in the range of from 10 to 50. In another embodiment,a portion of subsets is in the range of from 10 to 20. Examples of theabove embodiments are illustrated in FIGS. 1A and 1B.

As illustrated in FIG. 1A, nucleic acid (which may be DNA or RNA) isextracted from a sample containing T cells (100), after which inseparate reaction volumes, primers (102) specific for a nucleic acidsencoding TCRα's (or a portion thereof) and primers (104) specific fornucleic acids encoding TCRβ's (or a portion thereof) are combined underconditions that allow the respective nucleic acid populations to beamplified. e.g. by a two-stage polymerase chain reaction (PCR), such asdisclosed by Faham and Willis (cited above). Guidance and disclosuresfor selecting such primers and carrying out such reactions are describedextensively in the molecular immunology literature and below (for TCRβand IgH) and in references such as, Yao et al. Cellular and MolecularImmunology, 4: 215-220 (2007)(for TCRα), the latter reference beingincorporated herein by reference. In one embodiment, amplicons (106) and(108) produced by a two-stage PCR are ready for sequence analysis usinga commercially available next generation sequencer, such as MiSeqPersonal Sequencer (Illumnina, San Diego. Calif.). After nucleotidesequences have been determined (107) and (109), databases or tables (110and 112, respectively) are obtained. Like sequences may be counted andfrequency versus sequence plots (114 and 116) are constructed.Reconstituted TCRs may be determined by matching (118) TCRα's and TCRβ'swith identical frequencies or with frequencies having the same rankordering. Clearly, this embodiment of the method works most efficientlywhen frequencies of different TCRα's and TCRβ's are not too closetogether, i.e. are distinct, even taking into account experimentalerror.

Once a pair of clonotype sequences having equal (or equally ranked)frequencies are identified full length sequences encoding each chain maybe reconstructed from the known constant and variable regions usingconventional techniques for genetic manipulation and expression, e.g.Walchli et al. PLosOne. 6(11): e27930 (2011); or the like.

Greater accuracy in the determination of receptor chain frequencies maybe obtained in a variation of the above embodiment, which may be seen inreference to FIGS. 2A and 2B where RNA encoding TCRβ is amplified in atwo-staged PCR. As described more fully below, primer (202) and primerset (212) are used in a first stage amplification to attach commonprimer binding site (214) to all the nucleic acids encoding TCRβs. FIG.2B illustrates the components of a second stage amplification forgenerating more material and for attaching primer binding sites P5 (222)and P7 (220) which are used in cluster formation (via bridge PCR) in theSolexa-based sequencing protocol. Primer P7 (220) may also includesample tag (221) for multiplexing up to 96 samples for concurrentsequencing in the same run, e.g. Illumina application note 770-2008-011(2008). A different type of tag in the same primer may be used toincrease the accuracy of the determination of receptor chainfrequencies. In this embodiment, primer P7 is modified to include ahighly diverse tag set, so that instead of 96 tags, primer P7 isengineered to have 10,000 distinct tags, or more. In other words, primerP7 is a mixture of 10,000 or more distinct oligonucleotides each havingan identical template binding region, a distinct tag sequence, and anidentical 5′ tail portion (e.g., (223) in FIG. 2B). With thisarrangement, any subset of nucleic acids encoding the same receptorchain (e.g. less than 100) will receive a different tag with highprobability. Such a process of pairing members of a small set of nucleicacids with a much larger set of tags for counting, labeling, sortingpurposes is well known and is disclosed in various forms in thefollowing references that are incorporated by reference, Brenner, U.S.Pat. No. 6,172,214; Brenner et al, U.S. Pat. No. 7,537,897; andMacevicz, Internation patent publication WO US2005/111242; Brenner etal, Proc. Natl. Acad. Sci., 97: 1665-1670 (2000); Casbon et al, NucleicAcids Research, 39(12): e81 (2011); Fu et al, Proc. Natl. Acad. Sci.,108: 9026-9031 (2011). Construction of sets of minimallycross-hybridizing oligonucleotide tag, or tags with other usefulproperties, is disclosed in the following exemplary references, whichare incorporated by reference; Brenner, U.S. Pat. No. 6,172,214; Morriset al, U.S. patent publication 2004/0146901; Mao et al. U.S. patentpublication 2005/0260570; and the like. Preferably, the tag set shouldbe at least 100 times (or more) the size of the set of nucleic acids tobe labeled if all nucleic acids are to receive a unique tag with highprobability. For immune receptor chains, in one embodiment, the numberof distinct tags is in the range of from 10,000 to 100,000; in anotherembodiment, the number of distinct tags is in the range of from 10,000to 50,000; and in another embodiment, the number of distinct tags is inthe range of from 10,000 to 20,000. As disclosed in Brenner, U.S. Pat.No. 6,172,214, such large mixtures of oligonucleotide tags may besynthesized by combinatorial methods; alternatively, primers containingunique tags may be synthesized individually by non-combinatorialmethods, such as disclosed by Cleary et al, Nature Methods, 1: 241-248(2004); York et al, Nucleic Acids Research, 40(1): e4 (2012); LeProustet al, Nucleic Acids Research, 38(8): 2522-2540 (2010); and the like.

In one aspect, the above embodiment may be carried out by the followingsteps: (a) obtaining a sample containing T cells; (b) determiningnucleotide sequences of TCRα chains of T cells from the sample, eachTCRα chain having a frequency of occurrence in the sample; (c)determining nucleotide sequences of TCRβ chains of T cells from thesample, each TCR chain having a frequency of occurrence in the sample;and (d) identifying paired TCRα chains and TCRβ chains as those havingthe same frequency within the sample. Frequencies of the respective TCRαchains and TCRβ chains may be determined from the tabulations ofencoding nucleic acids, or clonotypes. Alternatively, frequencies of therespective TCRα chains and TCRβ chains may be determined from thetabulations of polypeptides encoded by the clonotypes. As mentionedabove, clonotype frequencies may be determined by counting clonotypesdirectly or indirectly by using a tagging scheme as described above.

FIG. 1B illustrates another embodiment for identifying matching receptorsubunits which may be applied to either TCRs or BCRs and which may beused even when receptor frequencies among subunit chains are close orindistinguishable, whether because of experimental error or otherwise.Starting with a sample containing lymphocytes (149), which may be eitherT cells or B cells, subsets are formed by separating or partitioning thesample into a plurality of subsets (152), 1 through K (in the figure).In some embodiments, only a portion of the K subset are analyzed; thus,it is not necessary to actually form all K subsets. One may form subsetsof only the portion that are actually analyzed. For example, if thesample has a volume of 100 μL and K=100, but only a portion consistingof 20 subset is to be analyzed, then only twenty 1 μL subsets need beformed. From each subset (152) nucleic acids encoding each differentimmune receptor chain (TCRα and TCRβ being shown under subset 1) aresequenced, thereby forming pairs of lists, for example, (162), (164),(166) and (168) for subsets 1, 2 . . . K−1, K, respectively. Each pairof such lists contains a first list of nucleotide sequences of a firstimmune receptor chain. e.g. list (154) for TCRα of subset 1, and asecond list of nucleotide sequences of a second immune receptor chain.e.g. list (156) for TCRβ of subset 1. In one embodiment, the number ofsubsets, K, is a number in the range of from 5 to 500; in anotherembodiment, K is a number in the range of from 10 to 100; in anotherembodiment, K is a number in the range of from 20 to 50. In someembodiments, a portion of subsets analyzed is 10 or fewer subsets; inother embodiments, a portion of subsets analyzed is 20 or fewer subsets;in other embodiments, a portion of subsets analyzed is at least fivepercent of the subsets; in other embodiments, a portion of subsetsanalyzed is at least ten percent of the subsets; in other embodiments, aportion of subsets analyzed is at least twenty percent of the subsets.

Each kind of lymphocyte in sample. e.g. lymphocyte (150), is present inthe sample at a particular frequency. The distribution of lymphocytesinto the subsets is readily approximated by a bionomial model; thus, foran arbitrary lymphocyte (for example (150)) having a particularclonotype, (a) its frequency in the sample, (b) the total number oflymphocytes in the sample, and (c) the number of subsets may be relatedto the expectation of finding at least one of the particular lymphocytein a predetermined fraction of subsets. This relationship may beexpressed as follows: r=(1−f)^((N/K)), where r is the fraction ofsubsets containing at least one of the particular lymphocyte, f is thefrequency of the particular lymphocyte in the sample, N is the totalnumber of lymphocytes in the sample, and K is the number of subsets.Thus, if one sets r=½ and takes N as a constant, then one may selectsuccessive values of K so that lymphocytes of different frequencies arepresent in about half of the subsets. Other values of r could beselected, but r=½ provides results with the highest statistical power,thus the value r˜½ is preferred. Once such lists are obtained they areexamined to identify pairs of first and second nucleotide sequences thateither occur in a subset together or are both absent from a subset. Byway of example, the members of pair (158) appear in lists (164) ofsubset 2 and in lists (166) of subset K−1, but neither member of thepair appears in lists (162) or (168) of subsets 1 and K, either alone ortogether. This of course reflects the presence or absence of theparticular lymphocyte that is in subsets 2 and K−1, but is absent fromsubsets 1 and K, such as lymphocyte (150). Such a pattern confirms thatthe members of pair (158) go together and correspond to the chains of afunctional immune receptor. Other lymphocytes in sample (149) may bepresent in approximately the same frequency, such as lymphocyte (153).However, the probability that at least one of lymphocyte (153) willoccur in exactly the same subsets as lymphocyte (150) is extremely low,especially if r is approximately one half and the portion of the Ksubsets analyzed is in the range of from 10 to 20, or more.

In one aspect of the invention, matched first and second chains oflymphocytes from a succession of frequency classes may be determined bycarrying out the above process repeatedly for different values of K. Forexample, a 1 mL sample of peripheral blood of a normal individualcontains about 1-4.8×10⁶ lymphocytes of which about 10-15 percent are Bcells, about 70-85 percent are T cells and about 10 percent are NKcells; thus, the 1 mL sample may contain from about 7×10⁶ to about 4×10⁵T cells. If the number of T lymphocytes in a 1 mL sample is N=10⁶, thenmatching TCR chains of T cells of the following frequencies are matchedby identifying those that appear together in fifty percent of thesubsets and not at all in the other fifty percent of subsets:

Frequency Number of Subsets Volume (μL) .001 1443 0.7 .0005 722 1.4.0001 144 6.9 .00005 72 13.9As mentioned above, not all the subsets at a particular frequency needbe analyzed. If there are a large number of lymphocytes that havefrequencies at or close to a selected frequency, e.g. f=0.001, they mayall be resolved by taking a larger and larger portion of the totalnumber of subsets until every pair that appears together in fiftypercent of the subsets can be distinguished from every other pair at thesame frequency. This is because the probability of two differentlymphocytes occurring in exactly the same subsets of the fifty percentbecomes infinitesimal as the portion of subsets is increased.

Identifying Paired and Unpaired T-Cell Receptor Chains WithAntigen-Specific Selection

In some embodiments, the invention is directed to identifyingantigen-specific T cells by one or a pair of immune receptor chains,such as TCRα, or TCRβ, or TCRα and TCRβ together; or TCRδ, or TCRγ, orTCRδ and TCRγ together. In some embodiments, the nucleotide sequenceencoding a single immune receptor chain, such as TCRβ, is used toidentify antigen-specific T cells. Sometimes such nucleotide sequencesare referred to herein as a “clonotype,” although clonotypes also may beordered pairs of nucleotide sequences specific to a particular T cell,such as the nucleotide sequences encoding the T cell's TCRα and TCRβchains, which may be represented (for example) as (S_(α), S_(β)), orlike notation, where S_(α) is a sequence of a segment of TCRα and S_(β)is a sequence of a segment of TCRβ, and as a pair they are a clonotypeof the cell they originate from.

Features of some embodiments of the invention are illustrated in FIG.1C. To a tissue sample (170) comprising T cells (173) is added antigen(171) under interaction conditions so that T cells specific for antigen(171) may interact with antigen (171). Such interaction may be direct orindirect. Direct interactions include binding of antigen (171) toantigen-specific T cells, binding of antigen peptide-multimer conjugatesto antigen-specific T cells, and the like. Peptide-multimer conjugates,such as tetramers, are well-known reagents to those of ordinary skill,e.g. Bousso, Microbes Infect. 2(4): 425-429 (2000). Kleneman et al.Nature Reviews Immunol., 2(4): 263-272 (2002); and the like. Indirectinteractions include presentation of antigen or antigen peptides toantigen-specific T cells by antigen presenting cells, such as, dendriticcells, artificial APCs, and the like. In some interactions,antigen-specific T cells may become activated T cells that mayproliferate and/or develop or express activation markers both of whichprovide means for selecting and/or enriching antigen-specific T cellsusing conventional techniques. Antigen (171) may comprise a wide varityof compounds or compositions as discussed more fully below. Proteins andpeptides derived from one or more proteins are of special interest,particularly when the proteins are associated with cancers or infectiousdiseases, such as bacterial or virus infections. Antigen (171) may becombined with, exposed to, or added to, tissue sample (170) in a varietyof ways known in the art, e.g. Berzofsky et al, J. Clin. Investigation,113: 1515-1525 (2004). After combining antigen (171) with tissue sample(170) in a reaction mixture, antigen-specific T cells (173) andnon-antigen-specific T cells alike are exposed to antigen (171) withwhich they interact either directly or indirectly.

In some embodiments, antigen-specific T cells (173) are activated,possibly after a period of incubation with antigen (171). A period ofincubation may vary widely. In some embodiments, incubation may be foran interval of from a few minutes (for example, 10 minutes) to an houror more; in other embodiments, incubation may be for an interval of afew hours (for example, 2 hours) to 8 or more hours. In otherembodiments, antigen-specific T cells (173) interact with antigen bybinding to or forming complexes with antigen or antigen reagents, suchas antigen peptide-multimer conjugates, such that activation may nottake place. A step of exposing may include the step of incubating atissue sample with an antigen. For example, in the case of a proteinantigen and a tissue sample that comprises PBMCs, a step of exposing mayinclude combining the tissue sample with peptides derived from theprotein antigen such that dendritic cells in the tissue sample presentthe peptides to antigen-specific T cells in the tissue sample which, inturn, interact with the antigen-presenting dendritic cells and areactivated. After exposing T cells (173) to antigen so thatantigen-specific T cells interact with antigen, antigen-specific T cellsmay be selected (172) and/or enriched based on some feature resultingfrom the interaction, such as antigen peptide-multimer binding,activation markers induced, proliferation of the T cells, or the like.As mentioned above, the step of selecting (172) antigen-specific T cellsmay be alternatively a step of enriching antigen-specific T cells fromthe reaction mixture, and/or a step of separating antigen-specific Tcells from the reaction mixture, and/or a step of isolatingantigen-specific T cells from the reaction mixture. Afterantigen-specific T cells are enriched, separated, and/or isolated (172)their clonotypes are determined by sequencing a predetermined segment ofa recombined nucleic acid that encodes a portion of an immune receptor,such as TCRβ and/or TCRα.

A predetermined segment chosen may vary widely; in some embodiments, itencompasses all or a portion of a V(D)J region, so that clonotypes basedthereon have maximal diversity for unique identification oft cellclones. Determination of clonotypes is described more fully below, butbriefly, recombined nucleic acids encoding one or more selected immunereceptors (such as TCRβ as shown in FIG. 1C) are sequenced (for example,by spatially isolating molecules thereof, amplifying such molecules, andcarrying out sequencing steps by a high-throughput sequencing chemistry,such as available with commercial next-generation DNA sequencers). As aresult of these sequencing steps, sequence reads (176) are producedwhich are used to determine clonotypes and clonotype frequencies ofantigen-specific T cells. Clonotypes and clonotype frequencies are alsodetermined either for T cells of the tissue sample (174) from sequencereads (178) or for non-antigen-specific T cells (175) from sequencereads (177). Non-antigen-specific T cells may be obtained from a two-waysorting procedure (for example, using FACS or MACS) based on T cellslabeled according to an interaction, such as, an interaction ofantigen-specific T cells with fluorescently labeled antigen peptidemultimers. These data may then be analyzed to identify clonotypesassociated with antigen-specific T cells, for example, as described inthe Example below and FIGS. 6-9. Briefly, in some embodiments,antigen-specific T cells may be associated with clonotype frequenciesthat increase in the selected population of T cells relative tofrequencies of the same clonotype in populations of non-antigen specificT cells or in the population of T cells in tissue sample (170).

Exemplary steps for implementing this embodiment of the invention (i.e.,for determining clonotypes associated with antigen-specific T cells in atissue sample) may include the following: (a) exposing the T cells ofthe sample to an antigen so that T cells specific for the antigeninteract with the antigen; (b) sequencing recombined nucleic acidsencoding a T-cell receptor chain or a portion thereof from a sample of Tcells from the tissue sample to provide sequence reads from whichclonotypes are determined; (c) isolating anigen-specific T cells fromthe tissue sample based on their interaction with the antigen; (d)sequencing recombined nucleic acids encoding a T-cell receptor chain ora portion thereof from a sample of the isolated antigen-specific T cellsto provide sequence reads from which clonotypes are determined; and (e)determining antigen-specific T cells in the tissue sample as T cellswhose clonotype frequencies increase in the sample of isolated T cellsrelative to the frequencies of the same clonotypes in a sample of Tcells in the tissue sample. In some embodiments, a step of exposing maybe carried out by reacting under interaction conditions an antigen witha tissue sample; in still other embodiments, a step of exposing may becarried out by reaction under activation conditions an antigen with atissue sample. As mentioned above the step of exposing for this andother embodiments may vary widely, and its implementation may depend onthe nature of the tissue sample and the nature of the antigen, as wellas other factors. For example, if a tissue sample includesantigen-presenting cells, such as dendritic cells, then exposing mayinclude either addition of an antigen, such as a protein, directly tothe tissue sample, or it may include producing antigenic material froman antigen of interest followed by addition of the antigenic material.More efficient T cell activation to a protein antigen, for example, maybe accomplished by exposing a tissue sample to a set of overlappingpeptides derived from the protein antigen of interest, usingconventional techniques. Alternatively, antificial antigen-presentingcompositions may be used in the exposing step or its equivalent, e.g.Oelke et al, Nature Medicine, 9(5): 619-624 (2003). The step of exposingT cells in a tissue sample may include exposing such T cells to wholecells containing antigen, to gene-modified cells expressing antigen, towhole protein, to peptides derived from a protein antigen, to viralvectors expressing an antigen, to antigen-modified, or loaded, dendriticcells. In some embodiments, a tissue sample is a blood sample; in otherembodiments, a tissue sample is a sample of peripheral blood mononuclearcells (PBMCs) derived from peripheral blood using conventionaltechniques. In some embodiments the step of exposing may be carried outby reacting under activation conditions a tissue sample comprising Tcells with an antigen, where various activation conditions are describedabove. In view of the wide variety of tissue samples and antigens, thestep of exposing may be alternatively carried out by a step of reactingunder activation conditions a tissue sample comprising T cells with anantigen.

Further exemplary steps for implementing the above method may comprise:(a) reacting under activation conditions a tissue sample comprising Tcells to an antigen; (b) sorting from the tissue sample activated Tcells and unactivated T cells; (b) sequencing recombined nucleic acidsencoding a T-cell receptor chain or a portion thereof from a sample of Tcells from the activated T cells to provide sequence reads from whichclonotypes are determined; (c) sequencing recombined nucleic acidsencoding a T-cell receptor chain or a portion thereof from a sample of Tcells from the unactivated T cells to provide sequence reads from whichclonotypes are determined; and (d) determining antigen-specific T cellsin the tissue sample as T cells whose clonotype frequencies increase inthe sample of activated T cells relative to the frequencies of the sameclonotypes in the tissue sample or in a sample of unactivated T cells.Likewise, exemplary steps for implementing the above method maycomprise: (a) reacting under interaction conditions a tissue samplecomprising T cells with an antigen; (b) sorting T cells of the tissuesample into a first subset of T cells that form complexes with theantigen or antigen reagents thereof and into a second subset of T cellsthat do not form complexes with the antigen or antigen reagents thereof;(b) sequencing recombined nucleic acids encoding a T-cell receptor chainor a portion thereof from a sample of the first subset to providesequence reads from which clonotypes are determined, (c) sequencingrecombined nucleic acids encoding a T-cell receptor chain or a portionthereof from a sample of T cells from the tissue sample or the secondsubset to provide sequence reads from which clonotypes are determined;and (d) determining antigen-specific T cells in the tissue sample as Tcells whose clonotype frequencies increase in the sample of T cells ofthe first subset relative to the frequencies of the same clonotypes inthe tissue sample or in a sample of T cells from the second subset. Asused herein, the term “antigen reagents” means reagents derived from anantigen designed to bind to, or form complexes with, T cells whose TCRsare specific for the antigen. Exemplary antigen reagents include, butare not limited to, multimers conjugated with peptides derived from anantigen.

In some embodiments, the above method of determining antigen-specific Tcells in a tissue sample may be carried out by steps comprising: (a)reacting under activation conditions in a reaction mixture a tissuesample comprising T cells to an antigen or antigen reagents thereof; (b)sequencing recombined nucleic acids encoding a T-cell receptor chain ora portion thereof from a sample of T cells from the reaction mixtureprior to addition of the antigen to the reaction mixture to providesequence reads from which clonotypes are determined; (c) incubating thereaction mixture after addition of the antigen or antigen reagentthereof for a predetermined interval; (d) sequencing recombined nucleicacids encoding a T-cell receptor chain or a portion thereof from asample of T cells from the incubated reaction mixture to providesequence reads from which clonotypes are determined; (d) determiningantigen-specific T cells in the tissue sample as T cells whose clonotypefrequencies increase in the incubated reaction mixture relative to thefrequencies of the same clonotypes in the reaction mixture prior to theaddition of antigen. In some embodiments, a predetermined interval forincubation is usually greater than eight hours; in other embodiments, apredetermined interval may be greater than 24 hours; in furtherembodiments, a predetermined interval may be within a range of from 8hours to 72 hours.

In some embodiments, step of isolating antigen-specific T cells may besubstituted with either a step of separating a sample ofantigen-specific T cells from the tissue sample after exposure to anantigen of interest or a step of recovering antigen-specific T cellsfrom the tissue sample after exposure to an antigen of interest. In someembodiments, such step of isolating may be carried out by sortingantigen-interacting and/or activated T cells from a tissue sample;likewise, in some embodiments, non-antigen-specific T cells and/orunactivated T cells may be sorted from a tissue sample. Such steps ofthe various embodiments may be carried out by a variety of methodsincluding, but not limited to, (i) peptide-MHC multimer stainingreagents (such as, tetramers, pentamers, or the like), followed bysorting, panning, or otherwise capturing complexes between such reagentsand antigen-specific T cells, (ii) sorting or panning or capturing basedon activation markers, such as CD137, CD154, or others (described morefully below), or (iii) proliferation (and therefore, for example, anincrease in frequency) of antigen-specific T cells overantigen-non-specific T cells. Thus, in some embodiments, said step ofisolating may comprise a step isolating activated T cells; or a step ofseparating activated T cells from the tissue sample. In some of suchembodiments, T cell activation markers, as noted above, may be used tosort, pan or otherwise capture activated T cells, using conventionaltechniques. Generally, a step is taken for obtaining a sample of T cellsfrom a pool of T cells derived from the tissue sample, which pool isenriched in antigen-specific T cells and/or activated T cells. In someembodiments, T cells with an activation marker may be sorted or isolatedusing a binding compound, such as an antibody, which specifically bindsto the activation marker and which can be directly or indirectly labeledin accordance with conventional methods, e.g. FACS, magnetic bead-basedseparation, or like techniques.

In another application of the above embodiment, T cell immunogenicitymay be measured in the following steps: (a) reacting under activationconditions a tissue sample comprising T cells with an antigen or anantigen reagent thereof; (b) sequencing recombined nucleic acidsencoding a T-cell receptor chain or a portion thereof from a sample of Tcells from the tissue sample exposed to antigen or antigen reagentsthereof to provide sequence reads from which clonotypes are determined;(c) isolating activated T cells from the tissue sample; (d) sequencingrecombined nucleic acids encoding a T-cell receptor chain or a portionthereof from a sample of the activated T cells isolated from the tissuesample to provide sequence reads from which clonotypes are determined;and (e) quantifying immunogenicity of the antigen as a function ofincreases in frequencies of clonotypes in the sample of isolated T cellsexposed to antigen with respect to frequencies of the same clonotypes inthe tissue sample prior to said step of isolating. Exemplary functionsof increases in frequencies of clonotypes include an average ofincreases among the isolated antigen-specific T cells; another exemplaryfunction of increases includes an average distance of data points ofclonotypes registering increases in frequency from the diagonal in plotssuch as those of FIG. 6, 7 or 8. Still another measure of T cellimmunogenicity includes any of several similarity measures of aclonotype profile of T cells of the exposed tissue sample prior toisolating and a clonotype profile of T cells of a sample of T cellsisolated (or separated) from the tissue sample, such as described inFaham et al. International patent publication WO/2013/036459, which isincorporated herein by reference. In this embodiment, antigens ofparticular interest are therapeutic proteins, such as therapeuticantibodies.

In one aspect, a similarity measure for use with these embodiments ofthe invention is a monotonically varying function that maps (or iscapable of mapping by a simple transformation) at least two sets ofclonotype frequency measurements (e.g. two sequence-based clonotypeprofiles) to the unit interval[0,1]. Simple transformations include, butare not limited to, any linear transformation of dependent variables,logarithmic transformations, such as y_(ij)=ln(n_(ij)+1) (where n_(ij)is the number of clonotype i in sample j), or the like. A value of zeromeans no similarity between clonotype profiles and a value of one meanstwo clonotype profiles are statistically identical. Exemplary similaritymeasures that may be implemented in these embodiments are described inLegendre and Legendre, Numerical Ecology (Elsevier, 1998); Magurran,Measurement of Biological Diversity (Wiley-Blackwell, 2003); Wolda,Occologia (Berl), 50: 296-302 (1981); and like references, which areincorporated by reference. Such similarity measures include, but are notlimited to, Czekanowski's index, Dice's coefficient, Horn's informationtheory index. Canberra metric. Morisita's index. Kaczynski's similarityindex. Sorensen's index, Jacquard's index, Bray-Curtis index, and thelike. In one aspect, similarity measures are similarity metrics; or inother words, the similarity measures employed have properties of adistance measure, such as, (i) the value of the measure is alwaysnon-negative, (ii) the measure is zero if and only if the clonotypeprofile measurements are identical, (iii) the value of the measure isinvariant with respect to the ordering of the clonotype profilemeasurements (sometimes expressed as d(x,y)=d(y,x)), (iv) the triangleinequality holds with respect to three different clonotype profilemeasurements. In another aspect, similarity measures may be correlationcoefficients (subject to a simple transformation, e.g. taking itsabsolute value, squaring its value, or the like, so that its value isrestricted to the unit interval). Exemplary correlation coefficientsinclude, but are not limited to, Pearson product-moment correlationcoefficient and rank correlations, such as Spearman's rank correlationcoefficient, Kendall's tau rank correlation coefficient, and the like.In one embodiment a Morisita-Horn index (C₁₃) (including Morisita-Hornindex with a logarithmic transformation), as disclosed in Wolda (citedabove), is employed with the embodiments.

Another embodiment for identifying pairs of immune receptor chains ofantigen-specific T cells is illustrated in FIG. 1D, where T cellcontaining reaction mixtures are exposed to a single antigen. Similarlyto the embodiment of FIG. 1B, a tissue sample is partitioned intosubsets (152) from 1 to K and a portion of the subsets may be selectedfor analysis. Ranges in the values of K and the portion selected may bethe same as for the embodiment of FIG. 1B. In one embodiment, as above,the partitions may be aliquots of the tissue sample, in whichapproximately equal amounts of tissue sample are provided to eachsubset, for example, by distributing equal amounts of tissue sample toeach of K reaction mixtures, which may be contained by vessels orreactors, such as wells in a multi-well plate. Tissue samples may alsobe distributed to a plurality of K separate chambers of a microfluidicsdevice in connection with this and/or the embodiments described above. Tcells of each subset are exposed to antigen (179) after which reactionmixtures in the K vessels are incubated for a time (for example, apredetermined interval) sufficient for T cells to respond to, orinteract with, the antigen, either directly or in a processed form (forexample, as an antigen reagent). Such response may include forming astable complex with antigen or a processed form thereof, or may includethe development and/or expression of activation markers by T cells, ormay include proliferation by T cells specific for the antigen.Antigen-interacting or antigen-responding T cells are then selected(180) and isolated (for example, sorted) from each of the K chambers,after which recombined nucleic acids encoding predetermined portions ofone or both TCR chains are sequenced to provide sequence reads fromwhich clonotypes and clonotype profiles (for example, 154 and 156) areformed. As above with the embodiment of FIG. 1B, once such profiles areobtained they are examined to identify pairs of first and secondnucleotide sequences that either occur in a subset together or are bothabsent from a subset. By way of example, the members of pair (181)appear in lists (184) of subset 2 and in lists (186) of subset K−1, butneither member of the pair appears in lists (182) or (188) of subsets 1and K, either alone or together. As above, this reflects the presence orabsence of a particular lymphocyte, which in this illustration is insubsets 2 and K−1, but is absent from subsets 1 and K. Such a patternconfirms that the members of pair (181) go together and correspond tothe chains of a functional immune receptor that is specific for antigen,Ag₁ (179).

In some embodiments, the above method of determining receptors ofantigen-specific T cells in a tissue sample may comprise the followingsteps: (a) partitioning a tissue sample containing T cells into aplurality of subsets; (b) exposing the T cells of each of a portion ofsubsets to an antigen so that T cells specific for the antigen areactivated; (c) isolating the activated T cells of each subset of theportion; (d) sequencing recombined nucleic acids encoding T-cellreceptor α chains in each subset of the portion to provide sequencereads from which α chain clonotypes are determined; (e) sequencingrecombined nucleic acids encoding T-cell receptor β chains in eachsubset of the portion to provide sequence reads from which β chainclonotypes are determined; and (f) identifying as antigen-specific Tcell receptors with those pairs of α chain clonotypes and β chainclonotypes that for every subset of the portion (i) either both the αchain clonotype and β chain clonotype are present in a subset or neitherare present in a subset, and (ii) both the α chain clonotype and β chainclonotype are present in at least one subset of the portion and the αchain clonotype and β chain clonotype are not present in at least onesubset of the portion.

Alternatively, in some embodiments, the above method of determiningreceptors of antigen-specific T cells in a tissue sample may comprisethe following steps: (a) forming a plurality of subsets from a tissuesample containing T cells; (b) reacting under activation conditions theT cells of each subset to an antigen; (c) isolating the antigen-specificT cells of each subset; (d) sequencing recombined nucleic acids encodingT-cell receptor α chains in each subset to provide sequence reads fromwhich α chain clonotypes are determined; (e) sequencing recombinednucleic acids encoding T-cell receptor β chains in each subset toprovide sequence reads from which β chain clonotypes are determined; (d)identifying as antigen-specific T cell receptors with those pairs of αchain clonotypes and β chain clonotypes that for every subset (i) eitherboth the α chain clonotype and β chain clonotype are present in a subsetor neither are present in a subset, and (ii) both the α chain clonotypeand β chain clonotype are present in at least one subset and the α chainclonotype and β chain clonotype are not present in at least one subset.In some of these latter embodiments, the a plurality of subsets formedmay correspond to a portion of the plurality into which a tissue sampleis partitioned in the former embodiments. In some embodiments, the stepof forming a plurality of subsets may comprise aliquoting portions of atissue sample into separate reaction vessels. In some embodiments, suchportions are equal portions.

Another embodiment for identifying clonotypes of antigen-specific Tcells is illustrated in FIGS. 5A-5B, where a plurality of antigens (500)is exposed to T cells in a plurality of different reaction mixtures. Inone aspect, this embodiment permits the identification ofantigen-specific T cells from scarce tissue samples, such as from acancer patient whose tissue sample will be used to identify clonotypesfor immune monitoring (e.g. minimal residual disease (MRD) analysis), toproduce a patient-specific immunotherapeutic reagent using cancerantigen-specific T cells, or the like. Subsets (or reaction mixtures)(502) from 1 to K (shown in FIGS. 5A-5B as 1-8) are formed from a tissuesample The number of different antigens employed may vary widely and insome embodiments the number depends on the nature of the antigens. Forprotein antigens, in some embodiments, a plurality of protein antigensmay be employed; in further embodiments, a plurality of protein antigensmay be in the range of from 2 to 100 protein antigens; in otherembodiments, a plurality may be in the range of from 2 to 50 proteinantigens; in other embodiments, a plurality may be in the range of from2 to 10 protein antigens; in still other embodiments, a plurality may bein the range of from 2 to 1000 protein antigens. Each antigen ofplurality (500) is exposed to (or presented to) T cells of asubplurality of reaction mixtures (502) less than the total plurality ofK reaction mixtures (in this illustration, subpluralities are each 4).Selections of the subsets of reaction mixtures into which antigens areplaced are predetermined for each antigen. In some embodiments, eachantigen is applied or exposed to a unique subplurality of subsets. Thatis, the selection of subsets making up a subplurality corresponding to aparticular antigen is unique to that antigen. The size of thesubpluralites may be the same or different for each antigen; but in someembodiments, the size of the subpluralities (i.e. the number of subsetsin each) are the same for each antigen (which is equal to 4 in FIGS.5A-5B). In some embodiments, subpluralities of subsets correspond to adifferent combination of subsets out of the plurality (in this case 8),as mentioned above. Thus, for some embodiments, the number of possiblesubsets is the same as the number of different combinations of R subsetsselected from the total number of subsets, K. (For example, for R=4 andK=8, the number of different combinations is K!i(R!(K−R)!).

A selection of different combinations (or subpluralities) for antigens(500) is indicated by matrix (506) of +'s and −'s which indicate whichantigen is exposed to T cells of which subsets. As mentioned above, theselection of subsets into which an antigen is applied (or exposed) ispredetermined; thus, for example, antigen Ag₁ is applied to subpluralityof subsets 1, 4, 5 and 7. A subplurality of subsets which are exposed toantigen may vary between 2 and K−1; however, in some embodiments, thesize of the subplurality is an integer equal to or closest to K/2. Asabove, after exposure to antigen and optional incubation,antigen-specific T cells are selected (504) (e.g. based on interactionwith with an antigen in the reaction mixture) and clonotype profiles aregenerated for recombined nucleic acids encoding a selected TCR chain ora portion thereof (as illustrated for subset 1), which permits itscorresponding T cell to be identified and/or isolated. Prior toexposure, a sample of T cells may be taken from the tissue samplesubsets (for example, 510). Recombined nucleic acids encoding clonotypesof the same TCR segment are sequenced both in sample (510) and in sample(511) to produce sequence reads (514) and (515) from which clonotypesand clonotype frequencies are determined. Frequencies of clonotypes thatincrease in the selected pools of T cells (illustrated as lists (520) inFIG. 5B) correspond to T cells specific for antigens (for example. Ag1or Ag4 in reaction mixture 1) An antigen-specific clonotype may beidentified by observing a clonotype that increases in frequency in everyreaction mixture of a given antigen. For example, in FIGS. 5A-5B, thesame clonotype (518a, 518b, 518c and 518d) is observed to have increasedin frequency within reaction mixtures 1, 4, 5 and 7 which corresponds tothe unique subplurality of subsets into which antigen 1 was added, butnot to have increased in the other reaction mixtures where antigen 1 wasabsent; therefore, clonotype (518) identifies a T cell with a TCRspecific for antigen 1. Likewise, the same clonotype (522a. 522b. 522cand 522d) is observed to have increased in frequency within reactionmixtures 1, 2, 3 and 8, which corresponds to the unique subplurality ofsubsets into which antigen 4 was added, but not to have increased infrequency in the other reaction mixtures where antigen 4 was absent;therefore, clonotype (522) identifies a T cell with a TCR specific forantigen 4. Since each antigen is exposed to T cells in a uniquesubplurality of reaction mixtures (or subsets), whenever the sameclonotype is observed in each reaction mixture of the uniquesubplurality, then the clonotype corresponds to a TCR specific for theantigen corresponding to the subplurality.

In one aspect, the above embodiments of the invention for determiningclonotypes of antigen-specific T cells in a tissue sample may be carriedout with the following steps: (a) forming a plurality of subsets from atissue sample containing T cells; (b) exposing under interactionconditions T cells in a subplurality of subsets to one or more antigensso that T cells specific for any of the one or more antigens are capableof interacting therewith, and wherein each different antigen is exposedto T cells in a different subplurality; (c) enriching theantigen-interacting T cells of each subset of a subplurality; (d)sequencing recombined nucleic acids encoding a T-cell receptor chain ora portion thereof from said enriched T cells in each subset of thesubplurality to provide sequence reads from which clonotypes aredetermined; (e) sequencing recombined nucleic acids encoding T-cellreceptor chain or a portion thereof from said T cells in each subset ofthe subplurality prior to said step of enriching or from non-enriched Tcells in each subset of the subplurality to provide sequence reads fromwhich clonotypes are determined; and (f) identifying a clonotype of a Tcell specific for an antigen of the one or more antigens as a clonotypewhose frequency increases in each subset of a subplurality correspondingto the antigen and does not increase in subsets outside of suchsubplurality. That is, in some embodiments, such clonotypes areidentified by observing the clonotypes in all reaction mixtures thatincrease in frequency (520 in FIG. 5B) and identifying clonotypes thatappear in each of the subsets of the subplurality corresponding to agiven antigen and that is absent in all of the other subsets. In otherwords, a clonotype of a T cell specific for an antigen increases infrequency only in the subsets or reaction mixtures to which the antigenwas added and not in the others. In some embodiments, a clonotype of anantigen-specific T cell may be identified whenever the frequency suchclonotype increases in substantially every subset of a subpluralitycorresponding to the antigen and does not increase in substantiallyevery other subset (every subset not part of the subplurality).

For clarity, FIG. 4 illustrates the process of selecting subpluralitiesof a plurality of subset in accordance with some embodiments of theinvention. Tissue sample (400) is separated into a plurality of subsets(402), for example, 10 as shown in FIG. 4. Tissue sample (400) may alsobe aliquoted into a plurality of subsets, or a plurality of subsets maybe formed from it, which may or may not use the entire amount of tissuesample (400). A subplurality of plurality (402) is a selection of fromtwo to nine subsets of plurality (402). In some embodiments, severalsubpluralities are selected that each have the same number of subsets,such as illustrated in FIG. 4, where each subplurality consists of fivesubsets. In some embodiments of the invention, a different antigen isexposed to T cells in subsets of a different subplurality. Thus, forexample, subplurality 1 may be exposed to antigen 1, subplurality 2exposed to antigen 2, and so forth. Consequently, in FIG. 4, subset 1 isexposed to antigen 1, antigen 3 and antigen 4; likewise, subset 2 isexposed to antigen 1 and antigen 2; and so forth.

Identification of Antigen-Specific T cell Clonotypes Using Single CellTechniques

In some embodiments, antigen-specific T cell clonotypes may beidentified using single cell techniques, such as disclosed in Faham andWillis, U.S. Pat. Nos. 8,236,503 and 8,507,205, which are incorporatedherein by reference. In one aspect, the step of selecting T cells thatinteract with antigen is carried out by disposing T cells exposed toantigen(s) into reactors so that a substantial fraction of reactorscontain a single T cell and a single labeled antigen reagent, usuallybound to a TCR of the T cell. An objective of these embodiments of theinvention is to carry out a polymerase cycling assembly (PCA) reaction(also sometimes referred to as a “linking PCR”) on individual cells inthe reactors to link their recombined nucleic acid sequences (e.g.,encoding a portion of a TCR) to a sequence tag that is associated with,or labels, an antigen reagent present in the reactor with the single Tcell The products of such linking are referred to herein as “fusionproducts.” After their generation, fusion products can be sequenced toidentify both the clonotype of the TCR and the sequence tag which, inturn, identifies the antigen reagent. FIG. 1E gives an overview on oneembodiment of the invention. Lymphoid cells (1010)(shown combined withantigen reagents (1000)) each have a distinct identifying nucleic acid(1012), which in the figure are exemplified (without any intention ofbeing limiting) as messenger RNAs (mRNAs)(1012), which in the threecells illustrated in the figure are labeled “C₁”, “C₂”, and “C₃”, toindicate that they are three different recombined nucleic acids uniqueto each cell, respectively. These recombined nucleic acids encode TCRs(for example, 1001) expressed on the surface of the respective T cells.As mentioned above, T cells (1010) are shown combined with antigenreagents (1000), which may be conventional multimers, such as tetramers,which are labeled with sequence tags (for example, 1003) that identifythe MHC and peptide portions of the antigen reagent (for example, asshown enclosed in dashed box 1004). Antigen reagent (1000) isexemplified with a conventional structure comprising a frameworkcomponent (1002), such as a streptavidin molecule; MHC linking moieties(such as, biotinylated peptides (for example, 1006)); and MHC-peptidecomplexes (1004).

Antigen reagent (1000) may also include sequence tag labels (such as,1003), which may be produced as taught by Kwong et al, U.S. Pat. No.8,394,590, which is incorporated herein by reference. The MHC andpeptide portion determines the specificity of the reagent for a TCR andvice versa. Antigen reagents (1000) are produced so that substantiallyevery different antigen reagent (e.g. every different multimer) has adifferent sequence tag. In some embodiments, sequence tags andMHC-peptide portions are selected so that with the knowledge of a tag'ssequence, the identity of the MHC-peptide portion can be uniquelydetermined. That is, for example, there is a one-to-one correspondencebetween a sequence tag and an MHC-peptide complex, so that (forexample), a sequence tag “X” indicates the presence of recombinednucleic acid “C₁”, a sequence tag “Y” indicates the presence ofrecombined nucleic acid “C.”, and a sequence tag “Z” indicates thepresence of recombined nucleic acid “C₁”. Antigen reagents (1000) arecombined (1008) with T cells (1010) in a reaction mixture and areincubated under antigen-interaction conditions which permit theformation of T cell-reagent complexes whenever a TCR is specific for anantigen reagent. After such incubation, cells are disposed (1016) insingle cell reactors, which may vary widely and may include, but not belimited to, plates with arrays of nanoliter-volume wells, microfluidicdevices, and the like, as described more fully below. In someembodiments, single cell reactors are aqueous micelles in an emulsion,such as illustrated (1017) in FIG. 1E, where a substantial fraction ofmicelles in the emulsion contain a single T cell together with a singleantigen reagent. In one aspect, single-cell emulsion (126) is generatedusing a microfluidic emulsion generator, such as disclosed by Zeng etal. Anal. Chen., 82: 3183-3190 (2010), or the like.

Reactors (1018) contain a PCA reaction mixture that, for example, maycomprise a nucleic acid polymerase, outer primers and linking primers(described more fully below), nucleoside triphosphates, a buffersolution, and the like. In some embodiments, a PCA reaction mixture mayalso include one or more cell lysing reagents, to give the foregoingreagents access to intracellular recombined nucleic acids, such asmRNAs. For each reactor (1018) containing a cell, PCA reaction (1020)generates fusion products (1022) that may comprise one or more pairs ofsequences, such that one member of the pair is a sequence tag and theother member is a predetermined recombined nucleic acid. In otherembodiments, fusion products may comprise triplets of sequences, orhigher order concatenations, for example, as taught by Faham and Willis.U.S. Pat. No. 8,507,205. In some embodiments of the method of theinvention, a single kind of fusion product may be generated for eachcell (or per reactor) or a plurality of different kinds of fusionproducts may be generated for each cell (or per reactor). Such pluralitymay be at least 2, or it may be in the range of from 2 to 500, or from 2to 200, or from 2 to 100, or from 2 to 20. In one embodiment, suchplurality may be in the range of from 2 to 10. In some embodiments, suchplurality is two.

After completion of PCA reaction (1020), emulsion (1017) is broken andfusion products (1026) are isolated (1024). Fusion products (1026) arerepresented in FIG. 1E as conjugates of sequence tags (X, Y or Z) andrecombined nucleic acids (e.g. clonotypes) (C₁, C₂ and C₃). A variety ofconventional methods may be used to isolate fusion products (1026) fromthe reaction mixture, including, but not limited to, columnchromatography, ethanol precipitation, affinity purification after useof biotinylated primers, gel electrophoresis, or the like. As part ofPCA reaction (1020) or after isolation (1024), additional sequences maybe added to fusion products (1026) as necessary for sequencing (1028).Sequencing may be carried out using a conventional high-throughputinstrument. e.g. Genome Analyzer IIx (Illumina, Inc. San Diego), or thelike.

Polymerase cycling assembly (PCA) reactions permit a plurality ofnucleic acid fragments to be fused together to form a single fusionproduct in one or more cycles of fragment annealing and polymeraseextension, e.g. Xiong et al. FEBS Micro biol. Rev., 32: 522-540 (2008).PCA reactions come in many formats. In one format of interest. PCAfollows a plurality of polymerase chain reactions (PCRs) taking place ina common reaction volume, wherein each component PCR includes at leastone linking primer that permits strands from the resulting amplicon toanneal to strands from another amplicon in the reaction and to beextended to form a fusion product or a precursor of a fusion product.PCA in its various formats (and under various alternative names) is awell-known method for fragment assembly and gene synthesis, severalforms of which are disclosed in the following references: Yon et al.Nucleic Acids Research, 17: 4895 (1989): Chen et al, J. Am. Chem. Soc.,116: 8799-8800 (1994); Stemmer et al, Gene, 164: 49-53 (1995); Hoover etal. Nucleic Acids Research, 30: e43 (2002); Xiong et al, BiotechnologyAdvances, 26: 121-134 (2008); Xiong et al. FEBS Microbiol. Rev., 32:522-540 (2008); and the like.

An exemplary (but not limiting) PCA format useful in the presentembodiments is described in FIG. 1F, which illustrates a PCA scheme forjoining two separate fragments A′ (1208) and B′ (1210) into a singlefusion product (1222). Fragment A′ (1208) is amplified with primers(1200) and (1202) and fragment B′ (1210) is amplified with primers(1206) and (1204) in the same PCR mixture. Primers (1200) and (1206) are“outer” primers of the PCA reaction and primers (1202) and (1204) arethe “inner” primers of the PCA reaction. Inner primers (1202) and (1204)each have a tail (1203 and 1205, respectively) that are notcomplementary to A′ or B′ (or adjacent sequences if A′ and B′ aresegments imbedded in a longer sequence). Tails (1203) and (1205) arecomplementary to one another. Generally, such inner primer tails areselected for selective hybridization to its corresponding inner primer(and not elsewhere); but otherwise such tails may vary widely in lengthand sequence. In one aspect, such tails have a length in the range offrom 8 to 30 nucleotides; or a length in the range of from 14 to 24nucleotides. As the PCRs progress (1212), product fragments A (1215) andB (1217) are produced that incorporate tails (1203) and (1205) into endregions (1214) and (1216), respectively. During the PCRs productfragments A (1215) and B (1217) will denature and some of the “upper”strands (1215a) of A anneal (1218) to lower strands (1217b) of B and the3′ ends are extended (1219) to form (1220) fusion product A-B (1222).Fusion product A-B (1222) may be further amplified by an excess of outerprimers (1200) and (1206). In some embodiments, the region of fusionproduct (1222) formed from tails (1203) and (1205) may include one ormore primer binding sites for use in later analysis, such ashigh-throughput sequencing. Typically, in PCA reactions theconcentrations of outer primers are greater than the concentrations ofinner primers so that amplification of the fusion product continuesafter initial formation. For example, in one embodiment for fusing twotarget nucleic acids outer primer concentration may be from about 10 to100) times that of the inner primers, e.g. 1 μM for outer primers and0.01 μM for inner primers. Otherwise, a PCA reaction may comprise thecomponents of a PCR.

Single Cell Analysis. As mentioned above, in some embodiments of theinvention, cells from a population are disposed in reactors eachcontaining a single cell. This may be accomplished by a variety oflarge-scale single-cell reactor platforms known in the an, e.g. Clarkeet al. U.S. patent publication 2010/0255471; Mathies et al, U.S. patentpublication 2010/0285975; Edd et al, U.S. patent publication2010/0021984; Colston et at, U.S. patent publication 2010/0173394; Loveet al, International patent publication WO2009/145925; Muraguchi et al.U.S. patent publication 2009/0181859; Novak et al, Angew. Chem. Int.Ed., 50: 390-395 (2011); Chen et al, Biomed Microdeviccs, 11: 1223-1231(2009); and the like, which are incorporated herein by reference. In oneaspect, cells are disposed in wells of a microwell array wherereactions, such as PCA reactions, take place; in another aspect, cellsare disposed in micelles of a water-in-oil emulsion, where micellesserve as reactors. Micelle reactors generated by microfluidics devices,e.g. Mathies et al (cited above) or Edd et al (cited above), are ofparticular interest because uniform-sized micelles may be generated withlower shear and stress on cells than in bulk emulsification processes.Compositions and techniques for emulsifications, including carrying outamplification reactions, such as PCRs, in micelles is found in thefollowing references, which are incorporated by reference; Becher,“Emulsions: Theory and Practice,” (Oxford University Press, 2001);Griffiths and Tawlfik. U.S. Pat. No. 6,489,103; Tawfik and Griffiths,Nature Biotechnology, 16: 652-656 (1998); Nakano et al, J.Biotechnology, 102: 117-124 (2003); Dressman et al. Proc. Natl. Acad.Sci., 100: 8817-8822 (2003); Dressman et al, U.S. Pat. No. 8,048,627;Berka et al. U.S. Pat. Nos. 7,842,457 and 8,012,690; Diehl et al, NatureMethods, 3: 551-559 (2006); Williams et al. Nature Methods, 3: 545-550(2006); Zeng et al. Analytical Chemistry, 82(8); 3183-3190 (2010);Micellula DNA Emulsion & Purification Kit instructions (EURx, Gdansk,Poland, 2011); and the like. In one embodiment, the mixture ofhomogeneous sequence tags (e.g. beads) and reaction mixture is addeddropwise into a spinning mixture of biocompatible oil (e.g., lightmineral oil, Sigma) and allowed to emulsify. In another embodiment, thehomogeneous sequence tags and reaction mixture are added dropwise into across-flow of biocompatible oil. The oil used may be supplemented withone or more biocompatible emulsion stabilizers. These emulsionstabilizers may include Atlox 4912, Span 80, and other recognized andcommercially available suitable stabilizers. In some embodiments, theemulsion is heat stable to allow thermal cycling, e.g., to at least 94°C., at least 95° C., or at least 96° C. Preferably, the droplets formedrange in size from about 5 microns to about 500 microns, more preferablyfrom about 10 microns to about 350 microns, even more preferably fromabout 50 to 250 microns, and most preferably from about 100 microns toabout 200 microns. Advantageously, cross-flow fluid mixing allows forcontrol of the droplet formation, and uniformity of droplet size.

In some embodiments, micelles are produced having a uniform distributionof volumes so that reagents available in such reactors result insimilarly amplified target nucleic acids and sequence tags. That is,widely varying reactor volumes, e.g. micelle volumes, may lead toamplification failures and/or widely varying degrees of amplification.Such failures and variation would preclude or increase the difficulty ofmaking quantitative comparisons of target nucleic acids in individualcells of a population, e.g. differences in gene expression. In oneaspect, micelles are produced that have a distribution of volumes with acoefficient of variation (CV) of thirty percent or less. In someembodiments, micelles have a distribution of volumes with a CV of twentypercent of less.

Cells of a tissue sample and antigen reagent may be suspended in areaction mixture prior to disposition into reactors. In one aspect, areaction mixture is a PCA reaction mixture and is substantially the sameas a PCR reaction mixture with at least one pair of inner (or linking)primers and at least one pair of outer primers. In some embodiments, astep of lysing cells may be accomplished by heating cells to atemperature of 95° C. or above in the presence of a nonionic detergent,e.g. 0.1% Triton X-100 or Tween-20, for a period prior to carrying outan amplification reaction. In one embodiment, such period of elevatedtemperature may be from 10-20 minutes. Alternatively, a step of lysingcells may be accomplished by one or more cycles of heating and cooling,e.g. 96° C. for 15 min followed by 10° C. for 10 min, in the presence ofa nonionic detergent. e.g. 0.1% Triton X-100 or Tween-20. Guidance forcarrying out a lysing step is disclosed in Brown et al, J. R. Soc.Interface 5: S131-S138 (2008).

Clearly many microfluidics device configurations may be employed togenerate micelles containing single cells, e.g. Zagoni et al. chapter 2.Methods of Cell Biology, 102: 25-48 (2011); Bronzes, chapter 10, Methodsof Cell Biology, 102: 105-139 (2011); Wiklund et al, chapter 14. Methodsof Cell Biology, 102: 177-196 (2011); Le Gac et al, chapter 7. Methodsof Molecular Biology, 853: 65-82 (2012); and the like.

In some embodiments, this aspect of the invention for determiningantigen-specific T cells may be implemented with the following steps:(a) exposing under interaction conditions a tissue sample containing Tcells to antigen reagents labeled with sequence tags; (b) disposing inmultiple reactors single T cells specifically bound to at least oneantigen reagent, each reactor containing a polymerase cycling assembly(PCA) reaction mixture comprising a pair of outer primers and one ormore pairs of linking primers, at least one pair of such outer andlinking primers being specific for a recombined nucleic acid encoding asegment of a TCR chain of the T cell and one or more pairs of such outerand linking primers being specific for a sequence tag attached to theantigen reagent; (c) performing a PCA reaction in the reactors to formfusion products comprising said recombined nucleic acids and saidsequence tag; (d) spatially isolating individual molecules of fusionproducts from the reactors; (e) sequencing the spatially isolated fusionproducts from the reactors to generate sequence reads from which pairsof clonotypes and sequence tags are determined; and (f) identifyingantigen-specificity of T cells by their clonotype and sequence tagpairs. In some embodiments, the reactors are aqueous micelles of awater-in-oil emulsion. In some embodiments, aqueous micelles aregenerated by a microfluidics device. In some embodiments, the reactorsare nanoliter wells in a planar substrate. In some embodiments, afurther step of lysing the single T cells in the reactors is carried outprior to performing the PCA reaction.

Antigens

An antigen may be any compound or composition capable of eliciting acell-mediated immune response (that is, an adaptive immune response),particularly in a mammal, such as a human. In some embodiments, anantigen may be any compound that can be recognized by a T cell in thecontext of the MHC molecule. More particularly, antigens include, but isnot limited to, cells, tissue extracts, tissue or cell lysates,proteins, individually or as a mixture, a plurality of proteins,peptides, mixtures of peptides, lipids, carbohydrates, sugars, and thelike. An antigen can be characteristic of a disease, such as aninfectious disease, an autoimmune disease, or a cancer. The antigen canbe, for example, a viral antigen, a bacterial antigen, a cancer antigen,etc. In some embodiments, an antigen is a cancer antigen or a viralantigen. By “cancer antigen” is meant any molecule (e.g., protein,peptide, lipid, carbohydrate, etc.) solely or predominantly expressed orover-expressed by a tumor cell or cancer cell, such that the antigen isassociated with the tumor or cancer.

A cancer antigen may be a cancer antigen of only one type of cancer ortumor, such that the cancer antigen is associated with or characteristicof only one type of cancer or tumor. Alternatively, a cancer antigen maybe a cancer antigen (e.g., may be characteristic) of more than one typeof cancer or tumor. For example, a cancer antigen may be expressed byboth breast and prostate cancer cells and not expressed at all bynormal, non-tumor, or non-cancer cells, or expressed only minimally. Acancer antigen may a melanoma cancer antigen or a breast cancer antigen.Exemplary cancer antigens include those of the group consisting ofgp100. MART-1, NY-ESO-1, a member of the MAGE family of proteins, e.g.,MAGE-A1, mesothelin. Tyrosinase, TRP-1. TRP-2, PMSA, Her-2, and p53.

An antigen may be a viral antigen. In some embodiments, “viral antigen”means those antigens encoded by a part of a viral genome which can bedetected by a specific immunological response. Viral antigens include,for example, a viral coat protein, an influenza viral antigen, an HIVantigen, a Hepatitis B antigen, or a Hepatitis C antigen.

An antigen can be naturally, artificially, synthetically, orrecombinantly produced. Thus, an antigen can be a synthetic,recombinant, isolated, and/or purified protein, polypeptide, or peptide.Methods of making or obtaining such antigens are known in the art. Forexample, suitable methods of de novo synthesizing polypeptides andproteins (e.g., antigenic polypeptides and proteins) are described inChan et al., Fmoc Solid Phase Peptide Synthesis, Oxford UniversityPress. Oxford, United Kingdom, 2005; Peptide and Protein Drug Analysis,ed. Reid, R., Marcel Dekker, Inc., 2000; Epitope Mapping, ed. Westwoodet al., Oxford University Press. Oxford. United Kingdom, 2000; and U.S.Pat. No. 5,449,752. Also, polypeptides and proteins (e.g., antigenicpolypeptides and proteins) can be recombinantly produced using nucleicacids which encode the polypeptide or protein using standard recombinantmethods. See, for instance, Sambrook et al., Molecular Cloning: ALaboratory Manual, 3rd ed. Cold Spring Harbor Press, Cold Spring Harbor,N.Y. 2001; and Ausubel et al., Current Protocols in Molecular Biology.Greene Publishing Associates and John Wiley & Sons, NY, 1994. Thenucleotide sequences of many antigens are known in the art and areavailable from the GenBank database of the National Center forBiotechnology Information (NCBI) website. Further, an antigen can beisolated and/or purified from a source, such as a plant, a bacterium, aninsect, a mammal, e.g., a rat, a human, etc. Methods of isolation andpurification are well-known in the art.

An antigen can be a free antigen, e.g., unbound antigenic peptide (e.g.,a free peptide), or can be a bound antigen, e.g., an MHC-peptidetetramer or an antigenic peptide presented by a carrier cell which waspulsed with the peptide.

In some embodiments, peripheral blood mononuclear cells (PBMCs) (forexample, which may be obtained from blood, for example, as a leukapherisproduct) from a subject may be cultured directly in the presence ofantigen, to load antigen presenting cells (APCs) among the PBMCs withthe antigen and to activate/stimulate antigen-specific T cells presentin the PBMC. In this regard. PBMC may be collected from an individual,contacted with an antigen of interest, such as a tumor antigen, or aviral lysate., etc. In this manner, the APCs present in the PBMCs areloaded with the antigen, which is then presented to the T cells presentin the sample. In some embodiments, antigen-specific T cells may beactivated with peptide-MHC tetramers, see for example Altman, et al.,Science 1998 Jun. 19; 280(5371):1821. In some embodiments, a proteinantigen may be exposed to T cells indirectly by generating a set ofpeptides for binding to MHC molecules, where the sequences of thepeptides are based on the amino acid sequence of the protein, e.g.Stickler et al, Toxicol. Sci., 77(2): 280-289 (2004). In some suchembodiments, peptides are overlapping peptides covering the protein. Insome embodiments, peptides each have a size of from 10 to 20 aminoacids.

T cells can be obtained from a number of sources, including peripheralblood mononuclear cells, bone marrow, thymus, tissue biopsy, tumor,lymph node tissue, gut associated lymphoid tissue, mucosa associatedlymphoid tissue, spleen tissue, or any other lymphoid tissue, andtumors. T cells can be obtained from T cell lines and from autologous orallogeneic sources. T cells may be obtained from a single individual ora population of individuals, for example, a population of individual whoall suffer from the same disease, such as, a cancer or an infectiousdisease.

In some embodiments, cells from the circulating blood of an individualare obtained by apheresis or leukapheresis. The apheresis producttypically contains lymphocytes, including T cells, monocytes,granulocytes. B cells, other nucleated while blood cells, red bloodcells, and platelets. In one embodiment, the cells collected byapheresis or leukapheresis may be washed to remove the plasma fractionand to place the cells in an appropriate buffer or media for subsequentprocessing steps. In one embodiment of the invention, the cells arewashed with phosphate buffered saline (PBS). In an alternativeembodiment, the wash solution lacks calcium and may lack magnesium ormay lack many if not all divalent cations. As those of ordinary skill inthe art would readily appreciate a washing step may be accomplished bymethods known to those in the art, such as by using a semi-automated“flow-through” centrifuge (for example, the Cobe 2991 cell processor.Baxter) according to the manufacturer's instructions. After washing, thecells may be resuspended in a variety of biocompatible buffers, such as,for example. Ca++/Mg++ free PBS. Alternatively, the undesirablecomponents of the apheresis sample may be removed and the cells directlyresuspended in culture media.

In other embodiments, T cells are isolated from peripheral bloodlymphocytes by lysing the red blood cells and by centrifugation througha PERCOLL™ gradient. A specific subpopulation of T cells, such as CD28+,CD4+, CD8+, CD45RA+, and CD45RO+T cells, can be further isolated bypositive or negative selection techniques. For example, CD3+, CD28+ Tcells can be positively selected using CD3/CD28 conjugated magneticbeads (e.g., DYNABEADS® M-450 CD3/CD28 T Cell Expander). In someembodiments, enrichment of a T cell population by negative selection canbe accomplished with a combination of antibodies directed to surfacemarkers unique to the negatively selected cells. One such method is cellsorting and/or selection via negative magnetic immunoadherence or flowcytometry that uses a cocktail of monoclonal antibodies directed to cellsurface markers present on the cells negatively selected. For example,to enrich for CD4+ cells by negative selection, a monoclonal antibodycocktail typically includes antibodies to CD14, CD20, CD11b, CD16,HLA-DR, and CD8.

Another method for preparing T cells for stimulation is to freeze thecells after the washing step, which does not require themonocyte-removal step. Wishing not to be bound by theory, the freeze andsubsequent thaw step provides a more uniform product by removinggranulocytes and, to some extent, monocytes in the cell population.After the washing step that removes plasma and platelets, the cells maybe suspended in a freezing solution. While many freezing solutions andparameters are known in the art and will be useful in this context, onemethod involves using PBS containing 20% DMSO and 8% human serum albumin(HSA), or other suitable cell freezing media. This is then diluted 1:1with media so that the final concentration of DMSO and HSA are 10% and4%, respectively. The cells are then frozen to −80° C. at a rate of 1°per minute and stored in the vapor phase of a liquid nitrogen storagetank.

Uses of Reconstituted TCRs

Reconstituted T cell receptors have a variety of uses both individuallyand as a group, including, but not limited to, as binding compounds forimmunotherapy, as components of transfected T cells for adoptiveimmunotherapy, as antigen sources in vaccines, and as indicators ofimmune status. Matched TCR chains in soluble format may be used as highaffinity binding compounds linked to T cell capturing agents for uniqueanti-cancer therapeutics. e.g. as taught by Jakobsen et al, U.S. Pat.Nos. 7,329,731 and 7,666,604; which are incorporated herein byreference. Matched TCR chains may be used to construct vectors whichmay, in turn, be used to transfect autologous T cells for adoptiveimmunotherapy of a patient. In one embodiment of this application,samples from which TCRs are analyzed may be taken before and after apatient has been immunized with a cancer antigen, so that elevatedanti-cancer TCR chains are readily matched and selected. Referencesdisclosing such applications include Turcotte et al, Adv. Surg., 45:341-360 (2011); Morgan et al, Science, 314: 126-129 (2006); Walchli etal. PlosOne, 6: e27930 (2011); Robbins et al, U.S. patent publication2010/0034834; and the like.

A population of matched or reconstituted TCRs from a sample comprises aunique profile of an individual's immune system, which contains muchmore information than profiles of single-sequence clonotypes. That is, apopulation of matched TCR chains or matched heavy and light chainimmunoglobulins comprises a clonotype profile where the clonotypes arepairs of nucleotide sequences that encode pairs of TCR chains expressedin the same T cell or pairs of heavy and light chain immunoglobulinsexpressed in the same B cell. In both cases, such pairs may be relateddirectly to T cell function, for example, by interaction with sets ofMHC tetramer-peptide complexes, e.g. Pahnowski et al, Immunol. Rev.,188: 155-163 (2002); Hadrup et al, Nature Methods, 6: 520-526 (2009), orto B cell function, for example, by ELISAs, e.g. Reddy et al, NatureBiotechnology, 28(9); 965-969 (2010). In one embodiment, clonotypeprofiles of matched immune receptor chains comprise at least 100clonotype pairs, wherein each clonotype of the pair comprises a sequenceof from 30 to 300 nucleotides. In another embodiment, clonotype profilesof matched immune receptor chains comprise at least 500 clonotype pairs,wherein each clonotype of the pair comprises a sequence of from 30 to30) nucleotides. In another embodiment, clonotype profiles of matchedimmune receptor chains comprise at least 1000 clonotype pairs, whereineach clonotype of the pair comprises a sequence of from 30 to 300nucleotides. In still another embodiment, such clonotype profiles ofmatched immune receptor chains comprise pairs of TCRα and TCRβclonotypes. In another embodiment, such clonotype profiles of matchedimmune receptor chains comprise pairs of TCRγ and TCRδ clonotypes.

Samples

Samples, or tissue samples, of T-cells (T lymphocytes) may include, forexample, helper T cells (effector T cells or Th cells), cytotoxic Tcells (CTLs), memory T cells, and regulatory T cells, as well as othercell types normally found in a tissue sample. In one aspect, a sample ofT cells includes at least 1,000 T cells: but more typically, a sampleincludes at least 10,000 T cells, and more typically, at least 100,000 Tcells. In another aspect, a sample includes a number of T cells in therange of from 1000 to 1,000,000 cells.

Samples used in the methods of the invention can come from a variety oftissues as noted above, including, for example, tumor tissue, blood andblood plasma, lymph fluid, cerebrospinal fluid surrounding the brain andthe spinal cord, synovial fluid surrounding bone joints, and the like.In one embodiment, the sample is a blood sample. The blood sample can beabout 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0, 1.5, 2.0, 2.5,3.0, 3.5, 4.0, 4.5, or 5.0 mL. The sample can be a tumor biopsy. Thebiopsy can be from, for example, from a tumor of the brain, liver, lung,heart, colon, kidney, or bone marrow. Any biopsy technique used by thoseskilled in the art can be used for isolating a sample from a subject.For example, a biopsy can be an open biopsy, in which general anesthesiais used. The biopsy can be a closed biopsy, in which a smaller cut ismade than in an open biopsy. The biopsy can be a core or incisionalbiopsy, in which part of the tissue is removed. The biopsy can be anexcisional biopsy, in which attempts to remove an entire lesion aremade. The biopsy can be a fine needle aspiration biopsy, in which asample of tissue or fluid is removed with a needle.

The sample can be a biopsy, e.g., a skin biopsy. The biopsy can be from,for example, brain, liver, lung, heart, colon, kidney, or bone marrow.Any biopsy technique used by those skilled in the art can be used forisolating a sample from a subject. For example, a biopsy can be an openbiopsy, in which general anesthesia is used. The biopsy can be a closedbiopsy, in which a smaller cut is made than in an open biopsy. Thebiopsy can be a core or incisional biopsy, in which part of the tissueis removed. The biopsy can be an excisional biopsy, in which attempts toremove an entire lesion are made. The biopsy can be a fine needleaspiration biopsy, in which a sample of tissue or fluid is removed witha needle.

As discussed more fully below, in some embodiments, a sample oflymphocytes is sufficiently large so that substantially every T cell orB cell with a distinct clonotype is represented therein, thereby forminga repertoire (as the term is used herein). In some embodiments, a sampleis taken that contains with a probability of ninety-nine percent everyclonotype of a population present at a frequency of 0.001 percent orgreater. In another embodiment, a sample is taken that contains with aprobability of ninety-nine percent every clonotype of a populationpresent at a frequency of 0.0001 percent or greater. In one embodiment,a sample of T cells includes at least a half million cells, and inanother embodiment such sample includes at least one million cells.

Blood samples are of particular interest and may be obtained usingconventional techniques, e.g. Innis et al, editors, PCR Protocols(Academic Press, 1990); or the like. For example, white blood cells maybe separated from blood samples using convention techniques. e.g.RosetteSep kit (Stem Cell Technologies, Vancouver, Canada). Bloodsamples may range in volume from 100 μL to 10 mL; in one aspect, bloodsample volumes are in the range of from 200 μL to 2 mL. Optionally,subsets of white blood cells, e.g. lymphocytes, may be further isolatedusing conventional techniques, e.g. fluorescently activated cell sorting(FACS)(Becton Dickinson, San Jose, Calif.), magnetically activated cellsorting (MACS)Miltenyi Biotec. Auburn, Calif.), or the like.

Since the identifying recombinations are present in the DNA of eachindividual's adaptive immunity cells as well as their associated RNAtranscripts, either RNA or DNA can be sequenced in the methods of theprovided invention. A recombined sequence from a T-cell encoding a Tcell receptor molecule, or a portion thereof, is referred to as aclonotype. The DNA or RNA can correspond to sequences from T-cellreceptor (TCR) genes. For example, the DNA and RNA can correspond tosequences encoding α, β, γ, or δ chains of a TCR. In a majority ofT-cells, the TCR is a heterodimer consisting of an α-chain and β-chain.The TCRα chain is generated by VJ recombination, and the β chainreceptor is generated by V(D)J recombination. For the TCRβ chain, inhumans there are 48 V segments, 2 D segments, and 13 J segments. Severalbases may be deleted and others added (called N and P nucleotides) ateach of the two junctions. In a minority of T-cells, the TCRs consist ofγ and δ delta chains. The TCR γ chain is generated by VJ recombination,and the TCR δ chain is generated by V(D)J recombination (Kenneth Murphy,Paul Travers, and Mark Walport, Janeway's Immunology 7th edition,Garland Science, 2007).

Amplification of Nucleic Acid Populations

Amplicons of target populations of nucleic acids may be generated by avariety of amplification techniques. In one aspect of the invention,multiplex PCR is used to amplify members of a mixture of nucleic acids,particularly mixtures comprising recombined immune molecules such as Tcell receptors, or portions thereof. Guidance for carrying out multiplexPCRs of such immune molecules is found in the following references,which are incorporated by reference: Faham and Willis, U.S. Pat. No.8,236,503 and U.S. Pat. No. 8,628,927; Morley, U.S. Pat. No. 5,296,351;Gorski, U.S. Pat. No. 5,837,447; Dau, U.S. Pat. No. 6,087,096; VonDongen et al. U.S. patent publication 2006/0234234; European patentpublication EP 1544308B1; and the like.

After amplification of DNA from the genome (or amplification of nucleicacid in the form of cDNA by reverse transcribing RNA), the individualnucleic acid molecules can be isolated, optionally re-amplified, andthen sequenced individually. Exemplary amplification protocols may befound in van Dongen et al, Leukemia, 17: 2257-2317 (2003) or van Dongenet al, U.S. patent publication 2006/0234234, which is incorporated byreference. Briefly, an exemplary protocol is as follows: Reactionbuffer: ABI Buffer II or ABI Gold Buffer (Life Technologies, San Diego,Calif.); 50 μL final reaction volume; 100 ng sample DNA; 10 pmol of eachprimer (subject to adjustments to balance amplification as describedbelow); dNTPs at 200 μM final concentration; MgCl₂ at 1.5 mM finalconcentration (subject to optimization depending on target sequences andpolymerase); Taq polymerase (1-2 U/tube); cycling conditions:preactivation 7 min at 95° C.; annealing at 60° C.; cycling times: 30 sdenaturation 30 s annealing; 30 s extension. Polymerases that can beused for amplification in the methods of the invention are commerciallyavailable and include, for example, Taq polymerase, AccuPrimepolymerase, or Pfu. The choice of polymerase to use can be based onwhether fidelity or efficiency is preferred.

Real time PCR, picogreen staining, nanofluidic electrophoresis (e.g.LabChip) or UV absorption measurements can be used in an initial step tojudge the functional amount of amplifiable material.

In one aspect, multiplex amplifications are carried out so that relativeamounts of sequences in a starting population are substantially the sameas those in the amplified population, or amplicon. That is, multiplexamplifications are carried out with minimal amplification bias amongmember sequences of a sample population. In one embodiment, suchrelative amounts are substantially the same if each relative amount inan amplicon is within five fold of its value in the starting sample. Inanother embodiment, such relative amounts are substantially the same ifeach relative amount in an amplicon is within two fold of its value inthe starting sample. As discussed more fully below, amplification biasin PCR may be detected and corrected using conventional techniques sothat a set of PCR primers may be selected for a predetermined repertoirethat provide unbiased amplification of any sample.

In one embodiment, amplification bias may be avoided by carrying out atwo-stage amplification (as described in Faham and Willis, cited above)wherein a small number of amplification cycles are implemented in afirst, or primary, stage using primers having tails non-complementarywith the target sequences. The tails include primer binding sites thatare added to the ends of the sequences of the primary amplicon so thatsuch sites are used in a second stage amplification using only a singleforward primer and a single reverse primer, thereby eliminating aprimary cause of amplification bias. Preferably, the primary PCR willhave a small enough number of cycles (e.g. 5-10) to minimize thedifferential amplification by the different primers. The secondaryamplification is done with one pair of primers and hence the issue ofdifferential amplification is minimal. One percent of the primary PCR istaken directly to the secondary PCR. Thirty-five cycles (equivalent to˜28 cycles without the 100 fold dilution step) used between the twoamplifications were sufficient to show a robust amplificationirrespective of whether the breakdown of cycles were: one cycle primaryand 34 secondary or 25 primary and 10 secondary. Even though ideallydoing only 1 cycle in the primary PCR may decrease the amplificationbias, there are other considerations. One aspect of this isrepresentation. This plays a role when the starting input amount is notin excess to the number of reads ultimately obtained. For example, if1,000,000 reads are obtained and starting with 1,000,000 input moleculesthen taking only representation from 100.000 molecules to the secondaryamplification would degrade the precision of estimating the relativeabundance of the different species in the original sample. The 100 folddilution between the 2 steps means that the representation is reducedunless the primary PCR amplification generated significantly more than100 molecules. This indicates that a minimum 8 cycles (256 fold), butmore comfortably 10 cycle (˜1,000 fold), may be used. The alternative tothat is to take more than 1% of the primary PCR into the secondary butbecause of the high concentration of primer used in the primary PCR, abig dilution factor is can be used to ensure these primers do notinterfere in the amplification and worsen the amplification bias betweensequences. Another alternative is to add a purification or enzymaticstep to eliminate the primers from the primary PCR to allow a smallerdilution of it. In this example, the primary PCR was 10 cycles and thesecond 25 cycles.

Generating Sequence Reads for Clonotypes

Any high-throughput technique for sequencing nucleic acids can be usedin the method of the invention. Preferably, such technique has acapability of generating in a cost-effective manner a volume of sequencedata from which at least 1000 clonotypes can be determined, andpreferably, from which at least 10,000 to 1,000,000 clonotypes can bedetermined. DNA sequencing techniques include classic dideoxy sequencingreactions (Sanger method) using labeled terminators or primers and gelseparation in slab or capillary, sequencing by synthesis usingreversibly terminated labeled nucleotides, pyrosequencing, 454sequencing, allele specific hybridization to a library of labeledoligonucleotide probes, sequencing by synthesis using allele specifichybridization to a library of labeled clones that is followed byligation, real time monitoring of the incorporation of labelednucleotides during a polymerization step, polony sequencing, and SOLIDsequencing. Sequencing of the separated molecules has been carried outby sequential or single extension reactions using polymerases or ligasesas well as by single or sequential differential hybridizations withlibraries of probes. These reactions have been performed on many clonalsequences in parallel including demonstrations in current commercialapplications of over 100 million sequences in parallel. These sequencingapproaches can thus be used to study the repertoire of T-cell receptor(TCR) and/or B-cell receptor (BCR). In one aspect of the invention,high-throughput methods of sequencing are employed that comprise a stepof spatially isolating individual molecules on a solid surface wherethey are sequenced in parallel. Such solid surfaces may includenonporous surfaces (such as in Solexa sequencing, e.g. Bentley et al,Nature, 456: 53-59 (2008) or Complete Genomics sequencing, e.g. Drmanacet al. Science, 327: 78-81 (2010)), arrays of wells, which may includebead- or particle-bound templates (such as with 454, e.g. Margulies etal, Nature, 437: 376-380 (2005) or Ion Torrent sequencing, U.S. patentpublication 20100137143 or 2010/0304982), micromachined membranes (suchas with SMRT sequencing, e.g. Eid et al, Science, 323: 133-138 (2009)),or bead arrays (as with SOLiD sequencing or polony sequencing, e.g. Kimet al, Science, 316: 1481-1414 (200)). In another aspect, such methodscomprise amplifying the isolated molecules either before or after theyare spatially isolated on a solid surface. Prior amplification maycomprise emulsion-based amplification, such as emulsion PCR, or rollingcircle amplification. Of particular interest is Solexa-based sequencingwhere individual template molecules are spatially isolated on a solidsurface, after which they are amplified in parallel by bridge PCR toform separate clonal populations, or clusters, and then sequenced, asdescribed in Bentley et al (cited above) and in manufacturer'sinstructions (e.g. TruSeq™ Sample Preparation Kit and Data Sheet,Illumina, Inc., San Diego. Calif, 2010); and further in the followingreferences: U.S. Pat. Nos. 6,090,592; 6,300,070; 7,115,400; andEP0972081B1; which are incorporated by reference. In one embodiment,individual molecules disposed and amplified on a solid surface formclusters in a density of at least 10′ clusters per cm²; or in a densityof at least 5×10⁵ per cm²; or in a density of at least 10⁶ clusters percm². In one embodiment, sequencing chemistries are employed havingrelatively high error rates. In such embodiments, the average qualityscores produced by such chemistries are monotonically decliningfunctions of sequence read lengths.

In one aspect, a sequence-based clonotype profile of an individual isobtained using the following steps: (a) obtaining a nucleic acid sample,for example, a sample containing T-cells of the individual; (b)spatially isolating individual molecules derived from such nucleic acidsample, the individual molecules comprising at least one templategenerated from a nucleic acid in the sample, which template comprises asomatically rearranged region or a portion thereof, each individualmolecule being capable of producing at least one sequence read; (c)sequencing said spatially isolated individual molecules to providesequence reads; and (d) determining abundances of different sequences ofthe nucleic acid molecules from the nucleic acid sample to generate theclonotype profile. In some embodiments, the step of sequencing includescoalescing at least a plurality of sequence reads to form eachclonotype. As described more fully below, such a step of coalescing is aprocess of combining sequence reads with error rates (for example, fromsequencing and/or amplification errors) to produce clonotypes that arecorrect with a high degree of likelihood, such as with a 99% confidencelevel.

In one aspect, for each sample from an individual, the sequencingtechnique used in the methods of the invention generates sequences ofleast 1000 sequence reads per nm; in another aspect, such techniquegenerates sequences of at least 10,000 sequence reads per run; inanother aspect, such technique generates sequences of at least 100,000sequence reads per run; in another aspect, such technique generatessequences of at least 500,000 sequence reads per run; and in anotheraspect, such technique generates sequences of at least 1,000,000sequence reads per run. From such sequence reads clonotypes aredetermined, for example, as described below, or as disclosed in Fahamand Willis (described above).

The sequencing techniques used in the methods generate sequence readshaving lengths of at least 30 nucleotides. In some embodiments, a stepof sequencing generates sequence reads having lengths of at least 50nucleotides; and in some embodiments, a step of sequencing generatessequence reads having lengths of at least 100 nucleotides.

Clonotype Determination from Sequence Data

Constructing clonotypes from sequence read data depends in part on thesequencing method used to generate such data, as the different methodshave different expected read lengths and data quality. In one approach,a Solexa sequencer is employed to generate sequence read data foranalysis. In one embodiment, a sample is obtained that provides at least0.5-1.0×10⁶ lymphocytes to produce at least 1 million templatemolecules, which after optional amplification may produce acorresponding one million or more clonal populations of templatemolecules (or clusters). For most high throughput sequencing approaches,including the Solexa approach, such over sampling at the cluster levelis desirable so that each template sequence is determined with a largedegree of redundancy to increase the accuracy of sequence determination.For Solexa-based implementations, preferably the sequence of eachindependent template is determined 10 times or more. For othersequencing approaches with different expected read lengths and dataquality, different levels of redundancy may be used for comparableaccuracy of sequence determination. Those of ordinary skill in the artrecognize that the above parameters. e.g. sample size, redundancy, andthe like, are design choices related to particular applications.

In one aspect of the invention, sequences of clonotypes (including butnot limited to those derived from TCRα, TCβ, TCRγ, and/or TCRδ, may bedetermined by combining information from a plurality of sequence readssequence reads, for example, along the V(D)J regions of the selectedchains. In another aspect, sequences of clonotypes are determined bycombining information from a plurality of sequence reads. Suchpluralities of sequence reads may include one or more sequence readsalong a sense strand (i.e. “forward” sequence reads) and one or moresequence reads along its complementary strand (i.e. “reverse” sequencereads).

Sequence reads of the invention may have a wide variety of lengths,depending in part on the sequencing technique being employed. Forexample, for some techniques, several trade-offs may arise in itsimplementation, for example, (i) the number and lengths of sequencereads per template and (ii) the cost and duration of a sequencingoperation. In one embodiment, sequence reads are in the range of from 20to 400 nucleotides; in another embodiment, sequence reads are in a rangeof from 30 to 200 nucleotides; in still another embodiment, sequencereads are in the range of from 30 to 120 nucleotides. In one embodiment,2 to 1000 sequence reads are generated for determining the sequence ofeach clonotype; in another embodiment, 2 to 100 sequence reads aregenerated for determining the sequence of each clonotype; and in anotherembodiment, 2 to 10 sequence reads are generated for determining thesequence of each clonotype; and in still another embodiment, at least 10sequence reads are generated for determining the sequence of eachclonotype. In the foregoing embodiments, the numbers given are exclusiveof sequence reads used to identify samples from different individuals.The lengths of the various sequence reads used in the embodimentsdescribed below may also vary based on the information that is sought tobe captured by the read; for example, the starting location and lengthof a sequence read may be designed to provide the length of an NDNregion as well as its nucleotide sequence; thus, sequence reads spanningthe entire NDN region are selected. In other aspects, one or moresequence reads that in combination (but not separately) encompass a Dand/or NDN region are sufficient.

In another aspect of the invention, sequences of clonotypes aredetermined in part by aligning sequence reads to one or more V regionreference sequences and one or more J region reference sequences, and inpart by base determination without alignment to reference sequences,such as in the highly variable NDN region. A variety of alignmentalgorithms may be applied to the sequence reads and reference sequences.For example, guidance for selecting alignment methods is available inBatzoglou. Briefings in Bioinformatics, 6: 6-22 (2005), which isincorporated by reference. In one aspect, whenever V reads or C reads(as mentioned above) are aligned to V and J region reference sequences,a tree search algorithm may be employed, e.g. as described generally inGusfield (cited above) and Cormen et al, Introduction to Algorithms,Third Edition (The MIT Press, 2009).

In another aspect, an end of at least one forward read and an end of atleast one reverse read overlap in an overlap region (e.g. 308 in FIG.3B), so that the bases of the reads are in a reverse complementaryrelationship with one another. Thus, for example, if a forward read inthe overlap region is “5′-acgttgc”, then a reverse read in a reversecomplementary relationship is “5′-gcaacgt” within the same overlapregion. In one aspect, bases within such an overlap region aredetermined, at least in part, from such a reverse complementaryrelationship. That is, a likelihood of a base call (or a related qualityscore) in a prospective overlap region is increased if it preserves, oris consistent with, a reverse complementary relationship between the twosequence reads. In one aspect, clonotypes of TCR β and IgH chains(illustrated in FIG. 3B) are determined by at least one sequence readstarting in its J region and extending in the direction of itsassociated V region (referred to herein as a “C read” (304)) and atleast one sequence read starting in its V region and extending in thedirection of its associated J region (referred to herein as a “V read”(306)). Overlap region (308) may or may not encompass the NDN region(315) as shown in FIG. 3B. Overlap region (308) may be entirely in the Jregion, entirely in the NDN region, entirely in the V region, or it mayencompass a J region-NDN region boundary or a V region-NDN regionboundary, or both such boundaries (as illustrated in FIG. 3B).Typically, such sequence reads are generated by extending sequencingprimers, e.g. (302) and (310) in FIG. 3B, with a polymerase in asequencing-by-synthesis reaction, e.g. Metzger, Nature Reviews Genetics,11: 31-46 (2010); Fuller et al, Nature Biotechnology, 27: 1013-1023(2009). The binding sites for primers (302) and (310) are predetermined,so that they can provide a starting point or anchoring point for initialalignment and analysis of the sequence reads. In one embodiment, a Cread is positioned so that it encompasses the D and/or NDN region of theTCR β or IgH chain and includes a portion of the adjacent V region, e.g.as illustrated in FIGS. 3B and 3C. In one aspect, the overlap of the Vread and the C read in the V region is used to align the reads with oneanother. In other embodiments, such alignment of sequence reads is notnecessary, e.g. with TCRβ chains, so that a V read may only be longenough to identify the particular V region of a clonotype. This latteraspect is illustrated in FIG. 3C. Sequence read (330) is used toidentify a V region, with or without overlapping another sequence read,and another sequence read (332) traverses the NDN region and is used todetermine the sequence thereof. Portion (334) of sequence read (332)that extends into the V region is used to associate the sequenceinformation of sequence read (332) with that of sequence read (330) todetermine a clonotype. For some sequencing methods, such as base-by-baseapproaches like the Solexa sequencing method, sequencing nm time andreagent costs are reduced by minimizing the number of sequencing cyclesin an analysis. Optionally, as illustrated in FIG. 3B, amplicon (300) isproduced with sample tag (312) to distinguish between clonotypesoriginating from different biological samples, e.g. different patients.Sample tag (312) may be identified by annealing a primer to primerbinding region (316) and extending it (314) to produce a sequence readacross tag (312), from which sample tag (312) is decoded.

Reducing a set of reads for a given sample to a set of distinctclonotypes and recording the number of reads for each clonotype would bea trivial computational problem if sequencing technology was error free.However, in the presence of sequencing errors, each genuine clonotype issurrounded by a ‘cloud’ of reads with varying numbers of errors withrespect to the its sequence. The “cloud” of sequencing errors drops offin density as the distance increases from the clonotype in sequencespace. A variety of algorithms are available for converting sequencereads into clonotypes. In one approach, coalescing of sequence reads(that is, merging candidate clonotypes determined to have one or moresequencing errors) depends on at least three factors: the number ofsequences obtained for each of the clonotypes being compared; the numberof bases at which they differ; and the sequencing quality score at thepositions at which they are discordant. A likelihood ratio may beconstructed and assessed that is based on the expected error rates andbinomial distribution of errors. For example, two clonotypes, one with150 reads and the other with 2 reads with one difference between them inan area of poor sequencing quality will likely be coalesced as they arelikely to be generated by sequencing error. On the other hand twoclonotypes, one with 100 reads and the other with 50 reads with twodifferences between them are not coalesced as they are considered to beunlikely to be generated by sequencing error. In one embodiment of theinvention, the algorithm described below may be used for determiningclonotypes from sequence reads. In one approach, sequence reads arefirst converted into candidate clonotypes. Such a conversion depends onthe sequencing platform employed. For platforms that generate high Qscore long sequence reads, the sequence read or a portion thereof may betaken directly as a candidate clonotype. For platforms that generatelower Q score shorter sequence reads, some alignment and assembly stepsmay be required for converting a set of related sequence reads into acandidate clonotype. For example, for Solexa-based platforms, in someembodiments, candidate clonotypes are generated from collections ofpaired reads from multiple clusters, e.g. 10 or more, as mentionedabove.

The cloud of sequence reads surrounding each candidate clonotype can bemodeled using the binomial distribution and a simple model for theprobability of a single base error. This latter error model can beinferred from mapping V and J segments or from the clonotype findingalgorithm itself, via self-consistency and convergence. A model isconstructed for the probability of a given ‘cloud’ sequence Y with readcount C₂ and E errors (with respect to sequence X) being part of a trueclonotype sequence X with perfect read count C₁ under the null modelthat X is the only true clonotype in this region of sequence space. Adecision is made whether or not to coalesce sequence Y into theclonotype X according the parameters C₁, C₂, and E. For any given C₁ andE a max value C₂ is pre-calculated for deciding to coalesce the sequenceY. The max values for C₂ are chosen so that the probability of failingto coalesce Y under the mill hypothesis that Y is part of clonotype X isless than some value P after integrating over all possible sequences Ywith error E in the neighborhood of sequence X. The value P is controlsthe behavior of the algorithm and makes the coalescing more or lesspermissive.

If a sequence Y is not coalesced into clonotype X because its read countis above the threshold C₂ for coalescing into clonotype X then itbecomes a candidate for seeding separate clonotypes (such as withcandidate clonotype 2. An algorithm implementing such principles wouldalso make sure that any other sequences Y2, Y3, etc. which are ‘nearer’to this sequence Y (that had been deemed independent of X) are notaggregated into X. This concept of ‘nearness’ includes both error countswith respect to Y and X and the absolute read count of X and Y, i.e. itis modeled in the same fashion as the above model for the cloud of errorsequences around clonotype X. In this way ‘cloud’ sequences can beproperly attributed to their correct clonotype if they happen to be‘near’ more than one clonotype.

In some embodiments, an algorithm proceeds in a top down fashion bystarting with the sequence X with the highest read count. This sequenceseeds the first clonotype. Neighboring sequences are either coalescedinto this clonotype if their counts are below the precalculatedthresholds (see above), or left alone if they are above the threshold or‘closer’ to another sequence that was not coalesced. After searching allneighboring sequences within a maximum error count, the process ofcoalescing reads into clonotype X is finished. Its reads and all readsthat have been coalesced into it are accounted for and removed from thelist of reads available for making other clonotypes. The next sequenceis then moved on to with the highest read count. Neighboring reads arecoalesced into this clonotype as above and this process is continueduntil there are no more sequences with read counts above a giventhreshold. e.g. until all sequences with more than 1 count have beenused as seeds for clonotypes.

As mentioned above, in another embodiment of the above algorithm, afurther test may be added for determining whether to coalesce acandidate sequence Y into an existing clonotype X, which takes intoaccount quality score of the relevant sequence reads. The averagequality score(s) are determined for sequence(s) Y (averaged across allreads with sequence Y) were sequences Y and X differ. If the averagescore is above a predetermined value then it is more likely that thedifference indicates a truly different clonotype that should not becoalesced and if the average score is below such predetermined valuethen it is more likely that sequence Y is caused by sequencing errorsand therefore should be coalesced into X. Successful implementation ofthe above algorithm for coalescing candidate clonotypes is dependentupon having an efficient way of finding all sequences with less than Eerrors (i.e. less than some sequence distance measure) from some inputsequence X. One approach is using a sequence tree. The implementation ofsuch trees has some unusual features in that the nodes of the tree arenot restricted to being single letters of the DNA sequences of thecandidate clonotypes. The nodes can have arbitrarily long sequences,which allows for a more efficient use of computer memory.

For example, all of the reads of a given sample are placed into thesequence tree. Each leaf nodes holds pointers to its associated reads. Aunique sequence of a candidate clonotype is retrieved by traversingbackwards in the tree from the leaf to the root node. The first sequenceis placed into a simple tree with one root node and one leaf node thatcontains the full sequence of the read. Sequences are next added one byone. For each added sequence either a new branch is formed at the lastpoint of common sequence between the read and the existing tree or addthe read to an existing leaf node if the tree already contains thesequence. Having placed all the reads into the tree it is easy to usethe tree for the following purposes: 1) Finding the highest read count;sorting leaf nodes by read count allows one to find the leaf node (i.e.sequence) with the most reads, and successively lower numbers of reads;2) Finding neighboring leafs: for any sequence all paths through thetree which have less than X errors with respect to this sequence aresearchable. A path is started at the root and branch this path intoseparate paths proceeding along the tree. The current error count ofeach path as proceeding along the tree is noted. When the error countexceeds the max allowed errors the given path is terminated. In this waylarge parts of the tree are pruned as early as possible. This is anefficient way of finding all paths (i.e. all leafs) within X errors fromany given sequence.

TCRβ Repertoire Analysis

In this example, TCRβ chains are analyzed and clonotypes are determined.The analysis includes amplification, sequencing, and analyzing the TCRβsequences. One primer is complementary to a common sequence in Cβ1 andCβ2, and there are 34 V primers capable of amplifying all 48 V segments.Cβ1 or Cβ2 differ from each other at position 10 and 14 from the J/Cjunction. The primer for Cβ1 and Cβ2 ends at position 16 bp and has nopreference for Cβ1 or Cβ2. The 34 V primers are modified from anoriginal set of primers disclosed in Van Dongen et al, U.S. patentpublication 2006/0234234, which is incorporated herein by reference. Themodified primers are disclosed in Faham et al, U.S. patent publication2010/0151471, which is also incorporated herein by reference.

The Illumina Genome Analyzer is used to sequence the amplicon producedby the above primers. A two-stage amplification is performed onmessenger RNA transcripts (200), as illustrated in FIGS. 2A-2B, thefirst stage employing the above primers and a second stage to add commonprimers for bridge amplification and sequencing. As shown in FIG. 2A, aprimary PCR is performed using on one side a 20 bp primer (202) whose 3′end is 16 bases from the J/C junction (204) and which is perfectlycomplementary to Cβ1(203) and the two alleles of Cβ2. In the V region(206) of RNA transcripts (200), primer set (212) is provided whichcontains primer sequences complementary to the different V regionsequences (34 in one embodiment). Primers of set (212) also contain anon-complementary tail (214) that produces amplicon (216) having primerbinding site (218) specific for P7 primers (220). After a conventionalmultiplex PCR, amplicon (216) is formed that contains the highly diverseportion of the J(D)V region (206, 208, and 210) of the mRNA transcriptsand common primer binding sites (203 and 218) for a secondaryamplification to add a sample tag (221) and primers (220 and 222) forcluster formation by bridge PCR. In the secondary PCR, on the same sideof the template, a primer (222 in FIG. 2B and referred to herein as“C10-17-P5”) is used that has at its 3′end the sequence of the 10 basesclosest to the J/C junction, followed by 17 bp with the sequence ofpositions 15-31 from the JC junction, followed by the P5 sequence (224),which plays a role in cluster formation by bridge PCR in Solexasequencing. (When the C10-17-P5 primer (222) anneals to the templategenerated from the first PCR, a 4 bp loop (position 11-14) is created inthe template, as the primer hybridizes to the sequence of the 10 basesclosest to the J/C junction and bases at positions 15-31 front the J/Cjunction. The looping of positions 11-14 eliminates differentialamplification of templates carrying Cβ1 or Cβ2. Sequencing is then donewith a primer complementary to the sequence of the 10 bases closest tothe J/C junction and bases at positions 15-31 from the J/C junction(this primer is called C′). C10-17-P5 primer can be HPLC purified inorder to ensure that all the amplified material has intact ends that canbe efficiently utilized in the cluster formation.)

In FIG. 2A, the length of the overhang on the V primers (212) ispreferably 14 bp. The primary PCR is helped with a shorter overhang(214). Alternatively, for the sake of the secondary PCR, the overhang inthe V primer is used in the primary PCR as long as possible because thesecondary PCR is priming from this sequence. A minimum size of overhang(214) that supports an efficient secondary PCR was investigated. Twoseries of V primers (for two different V segments) with overhang sizesfrom 10 to 30 with 2 bp steps were made. Using the appropriate syntheticsequences, the first PCR was performed with each of the primers in theseries and gel electrophoresis was performed to show that all amplified.

As illustrated in FIG. 2A, the primary PCR uses 34 different V primers(212) that anneal to V region (206) of RNA templates (200) and contain acommon 14 bp overhang on the 5′ tail. The 14 bp is the partial sequenceof one of the Illumina sequencing primers (termed the Read 2 primer).The secondary amplification primer (220) on the same side includes P7sequence, a tag (221), and Read 2 primer sequence (223) (this primer iscalled Read2_tagX_P7). The P7 sequence is used for cluster formation.Read 2 primer and its complement are used for sequencing the V segmentand the tag respectively. A set of 96 of these primers with tagsnumbered 1 through 96 are created (see below). These primers are HPLCpurified in order to ensure that all the amplified material has intactends that can be efficiently utilized in the cluster formation.

As mentioned above, the second stage primer. C-10-17-P5 (222, FIG. 2B)has interrupted homology to the template generated in the first stagePCR. The efficiency of amplification using this primer has beenvalidated. An alternative primer to C-10-17-P5, termed CsegP5, hasperfect homology to the first stage C primer and a 5′ tail carrying P5.The efficiency of using C-10-17-P5 and CsegP5 in amplifying first stagePCR templates was compared by performing real time PCR. In severalreplicates, it was found that PCR using the C-10-17-P5 primer had littleor no difference in efficiency compared with PCR using the CsegP5primer.

Amplicon (230) resulting from the 2-stage amplification illustrated inFIGS. 2A-2C has the structure typically used with the Illumina sequenceras shown in FIG. 2C. Two primers that anneal to the outmost part of themolecule, Illumina primers P5 and P7 are used for solid phaseamplification of the molecule (cluster formation). Three sequence readsare done per molecule. The first read of 100 bp is done with the C′primer, which has a melting temperature that is appropriate for theIllumina sequencing process. The second read is 6 bp long only and issolely for the purpose of identifying the sample tag. It is generatedusing a tag primer provided by the manufacturer (Illumina). The finalread is the Read 2 primer, also provided by the manufacturer (Illumina).Using this primer, a 100 bp read in the V segment is generated startingwith the 1st PCR V primer sequence.

Example

In this example steps common to some embodiments, such as the embodimentof FIG. 1C, are described for particular applications, including but notlimited to, exposing a tissue sample comprising T cells to antigen,activating T cell in a tissue sample by antigen, obtaining recombinednucleic acids from T cells of a tissue sample, isolating (or recovering,or sorting, or separating) activated T cells, sequencing recombinednucleic acids, forming clonotypes, and determining clonotypes ofantigen-specific T cells.

Tissue Samples. Characterized PBMCs were purchased from CellularTechnology Limited. Cells were thawed, washed and either lysed with RLTplus buffer (Qiagen) for nucleic acid purification or cultured overnightin the presence of peptides (see below) to identify antigen-specific Tcells.

Antigen-Specific T Cell Assays. Flow Cytometry and Cell Sorting.Antigen-specific cells were identified using a variety of assays:pentamer binding, cell surface marker upregulation (CD137, CD107)following short-term peptide incubation, and proliferation followingrelatively long-term peptide incubation. Pentamer-specific T cells wereidentified by incubating PBMCs with HCMV pp65₄₉₅₋₅₀₄ Pentamer(ProImmune) according to manufacturer's instructions. The procedures forobtaining viable antigen-specific T cells based on acquisition of thecell surface markers CD137/107 (for CD8 antigen-specific T cells)following brief in vitro incubation with peptides are well-known, e.g.Chattopadhyay et al, Nature Medicine, 11: 1113-1117 (2005); Meier et al,Cytometry A, 73: 1035-1042 (2008); Wolfl et al, Blood, 110: 201-210(2007); Wolfl et al. Cytometry A, 73: 1043-1049 (2008); and the like.Briefly, complete media containing 15% Fetal Bovine Serum (FBS),non-essential amino acids, glutamine and antibiotics was used forpeptide incubations. Thawed PBMCs were washed and suspended at ˜400,000cells per well (96-well i-bottom plates) in complete media. Unconjugatedantibodies directed against CD28 and CD49d were then added to the wellscontaining the suspended cells. Peptides derived from CMV pp65 (HCMVA(pp65) (JPT Peptide Technologies) were added directly to thecell/antibody mixture, according to manufacturer's instructions. Asingle peptide derived from CMV pp65 (sequence NLVPMVATV: hereinreferred to as ‘pp65₄₉₅’) was used at 2 μg/ml, pp65 ‘PepMix” and CEF+peptide pools (JPT Peptide Technologies) were added directly to thecell/antibody mixture, according to manufacturer's instructions.Following addition of peptides, cells were incubated at 37° C. for ˜18hours. Negative control incubations were prepared as outlined abovewithout addition of peptides. At the end of the incubation, cells wereharvested from the culture and stained with antibodies for analysis andsorting by flow cytometry. For each CD8 antigen-specific assay (CD137and CD107), fluorescently conjugated antibodies to the following cellsurface markers were used for flow cytometry: CD8, CD3 and either CD137or CD107a and CD107b. Cells were then washed and suspended in PBScontaining FBS (2%) and 4′,6-diamidino-2-phenylindole (DAPI) forexclusion of non-viable cells. Carboxyfluorescein diacetate,succinimidyl ester (CFSE)-labeled PBMCs were incubated as outlined abovefor 6 days in the presence of peptide and antibodies directed againstCD28 and CD49d. Antigen-specific CD8+ T cells were identified and sortedbased on CFSE dilution at day 6. Cells were acquired and sorted using aFACSAria (BD Biosciences) instrument. Sorted antigen-specific(CD3+CD8+CMVpentamer+, CD3+CD8+CD137+, CD3-3+CD8+CD107a/b+, orCD8+CFSE^(low)) and non-antigen-specific (CD3+CD8+CD137−,CD3+CD8+CD107a/b−) cells were pelleted and lysed in RLT Plus buffer fornucleic acid isolation. Analysis of flow cytomeay data files wasperformed using FlowJo (Ashland. Oreg.).

RNA and cDNA Preparation. RNA (and DNA) was isolated using AllPrepDNA/RNA mini and/or micro kits, according to manufacturer's instructions(Qiagen). RNA was reverse transcribed to cDNA using Vilo kits (LifeTechnologies).

TCRβ Amplification and Sequencing, cDNA was amplified using locusspecific primer sets for TCRβ. This amplification reaction reproduciblyamplified all possible RNA transcripts found in the sample containingthe rearranged TCRβ locus regardless of which variable (V) segment andwhich common constant (C) region allele each rearranged moleculepossessed, while appending the necessary sequences for cluster formationand sample indexing.

First stage primers were designed so as to allow for the amplificationof all known alleles of the germline sequences, as described above andin the following; Faham et al, Blood, 120: 5173-5180 (2012). At the 5′ends of the V segment primers, universal sequences complementary tosecond stage PCR primers were appended. Primers were optimized such thateach possible V and C segment was amplified at a similar rate so as tominimally skew the repertoire frequency distribution during theamplification process. Specificity of the primers was, in contrast, notoptimized as the primer sequences could be mapped and removed from theeventual sequence read. Thus a given sequence may have been amplified bymultiple primers.

In the second stage PCR, primers on the C side annealed to the C segmentwith a 5′ tail that contained the sequence primer and the P5 sequenceused for cluster formation in the Illumina Genome Analyzer sequencer.Primers on the V side annealed to the V segment with a 5′ tail thatcontained the sequence primer and the P7 sequence used for clusterformation. For each sample, one pair of primers is used in the secondstage. On the C side, it is always the same primer. On the V side, it isone of a set of primers which differs by a 6 base index. Specifically,the primers on the V side of the amplification constituted one of a setof primers, each of which had a 3′ region that annealed to the overhangsequence appended in the first reaction but which further contained oneof multiple 6 base pair indices that allowed for sample multiplexing onthe sequencer. Each of these primers further contained a 5′ tail withthe P7 sequence used for cluster formation in the Illumina GenomeAnalyzer sequencer.

First stage PCR was carried out using a high fidelity polymerase(AccuPrime, Life Technologies) for 16 cycles. A second stage PCR wascarried out for 22 cycles on 1/100 of the amplification products fromthe first stage PCR. Each sample contained a unique identifying tag.Samples were pooled and purified using the QIAquick PCR purification kit(Qiagen). Cluster formation and sequencing in both directions wascarried out per the manufacturer protocol (Illumina, Inc., La Jolla.Calif.). Specifically, three sequencing reactions were performed. First115 bp were sequenced from the C side sufficient to sequence through thejunctional sequence from C to V. At this point, the synthesized strandwas denatured and washed off. A second sequencing primer was annealedthat allowed the sample index to be sequenced for 6 cycles to identifythe sample. At this point the reverse complement strand was generatedper the Illumina protocol. A final sequencing read of 95 bp was obtainedfrom the V- to-C direction providing ample sequence to map the V segmentaccurately. The sequencing data was then analyzed to determine theclonotype sequences, as described above.

Clonotype Determination. A clonotype was defined when at least 2identical sequence reads were obtained. Briefly, after exclusion of lowquality reads, sequence data were then analyzed to determine theclonotype sequences including mapping to germline V and J consensussequences. First, the sample index sequences were used to identify whichof the sequences originate from which of the pooled samples. Sequenceswhose index were not a perfect match to one of the indices used in aspecific run were excluded. Next the forward read was used to map the Jsegment. Since all the sequences started from the same position of the Jsegments, all the J segments started at a predefined sequencingposition. The first 25 bp of the J segments were used to map the Jsegment. Any read with more than 5 high quality mismatches to the knownJ segments was excluded from further analysis.

After J segment identification, V segments were mapped. The reverse readwas used for this purpose. First, the V primer was mapped and excluded.Thereafter, the next 70 bases of the reverse read were mapped to theknown V segments. Reads that did not map to J and V segments wereexcluded. The next step in mapping involved identifying the frame thatrelated the forward and reverse reads and this allowed a continuoussequence from J to V to be constructed. This was done using the last 15bases of the forward read which were reliably within the V segmentregardless of NDN length. While these bases could be of relatively lowersequence quality as they were at the terminal end of a long read, theycould be used to map within a single identified V segment in order toidentify the position at which the two reads could be joined. Finally,the known V and J sequences to which the reads map were used to identifythe point in the forward read at which the sequences at the junctionsdiverged from these mapped segments.

Following clonotype determination, relative frequencies of theclonotypes were analyzed in the unsorted, antigen-specific andnon-antigen-specific populations. Clonotype frequency comparisonsbetween two samples are shown in several figures. Clonotypes that arepresent in sample A but not in sample B (where frequencies in sample Aand B are being compared) are represented to have the frequency of aclonotype with a single read in sample B. Therefore the frequency of themissing clonotype in a sample depends on the sequencing depth of aparticular sample. In these cases where a clonotype is missing in asample, because the frequency of a single read is assigned to theseclonotypes, the observed frequency is overestimated. Thus, in the vastmajority of these cases, the real clonotype frequency is likely to beoverestimated. Clonotypes absent in both samples appear where the axesintersect. Clonotypes present in one sample but not the other howeverlie along either the x- or y-axis.

Clonotypes from the antigen-specific T cell analyses were selected basedon the following three criteria. First, clonotypes had frequencies thatwere at least 10-fold increased in sorted antigen-specific versusnon-antigen-specific or unsorted cells. e.g. FIG. 6 panels A and B.Second, these clonotypes were also at lower frequency in sorted “notantigen-specific” cells compared to unsorted cells if greater than1/100,000 in order to avoid sub-sampling error (Poisson noise)associated with very low frequency clonotypes in sorted samples. Third,because of the limited number of input antigen-specific cells aftersorting (generally less than <30,000 cells), a greater than ‘20-cell’equivalent threshold was applied based on the relatively low inputnumber of cells in these samples. This minimum threshold enabledexclusion of clonotypes that appeared enriched in sortedantigen-specific samples but were due only to the presence of one or afew cells in the sample. For example, consider a sorted population of10,000 pentamer+ cells out of a sample with a million T cells. If asingle cell with a frequency of 1 per million in the unsorted sample isincidentally sorted in the pentamer+ sample, its frequency in the sortedsample will be 1/10,000 and would appear to be 100 fold enriched in thepentamer+ sample compared to the unsorted sample. To ameliorate thisproblem, a clonotype was required to represent 20 cells in the sortedpentamer+ sample. Specifically, the log 10 frequency threshold requiredin the pentamer+ sample was calculated as log 10(1(n/20)), where n isthe number of input sorted cells for that sample as determined by flowcytometry (For example, in FIG. 7 panel A, 16,281 is number of inputsorted cells and the calculated threshold frequency is 10^(−2.9)). Thosesequences meeting the three criteria outlined above were classified asantigen-specific T cell clonotypes.

Results. The combination of sorting and sequencing was used to identifyantigen-specific clonotypes in an individual with a known positiveresponse to a cytomegalovirus (CMV) antigen. First, TCRβ sequencing waspaired with a multimer-based immune assay to validate this method foridentification of antigen-specific CD8 TCRβ clonotypes. A peptidederived from CMV pp65(495-404) (referred to herein as the “pp65₄₉₅peptide”) is an HLA-A*0201 restricted immunodominant epitope thatinduces responses in CMV-positive individuals. To directly identify Tcells specific to this antigen, a commercially available pentamerreagent containing pp65 peptide bound to an MHC molecule was used. Inprinciple, all of the T cells carrying the sequences that bind thepentamer should be detected irrespective of their functional potential.pp65₄₉₅-specific CD8 T cells were identified by sequencing the TCRβrepertoire of cells that were sorted based on pentamer binding(pentamer+).

Frozen PBMCs were obtained from an individual with a characterizedresponse to pp65₄₉₅ by ELISPOT assay. Two populations were sorted fromthis individual: CD8 pentamer+ and pentamer− T cells. Nucleic acidsencoding TCRβ clonotypes were sequenced in these two populations alongwith the unsorted PBMC sample, so that the relative frequencies of theclonotypes in each population could be determined. Three criteria wereused to identify pp65₄₉₅-specific TCRβ clonotypes: 1) Clonotypes thatare enriched (i.e. have substantially higher frequency) in the pentamerpopulation compared to the pentamer− population; 2) Clonotypes that areenriched in the pentamer+ population compared to the unsorted sample;and 3) Clonotypes that are de-enriched (i.e. have lower frequency) inthe pentamer− population compared to the unsorted sample.

Eight clonotypes were identified that are substantially enriched (˜1,000fold) in the pentamer+ compared to the pentamer− population (FIG. 6panel A). The frequencies of these clonotypes were compared in thepentamer+ and the unsorted populations (FIG. 6 panel B). The highest ofthese clonotypes has a frequency of 0.81% in the unsorted sample, whichis consistent with the expected elevated response to pp65₄₉₅ in thisindividual. However, several of the other clonotypes were present at alevel below 10⁻⁴. The 8 clonotypes are enriched in the pentamer+population by a factor of ˜100 fold compared to their frequency inunsorted PBMC.

PBMCs from the same individual were used to assess whether immune assaysthat rely on indirect or functional changes in the T cells followingantigen stimulation are effective for identification of pp65₄₉₅-specificCD8 TCRβ clonotypes. PBMCs were stimulated with pp65₄₉₅ followed by flowcytometry 18 hours after the stimulation to capture cells based onexpression of the activation marker CD137. The TCRβ repertoire wasamplified and sequenced from sorted CD137+ and CD137− cells. Thecriteria for identification of pp65₄₉₅− specific TCRβ clonotypes withthis assay was similar to that used in the pentamer assay. Specifically,pp65₄₉₅− specific TCR clonotypes were expected to be present at muchhigher frequencies in the CD137+ population compared to the CD137−population.

Nine clonotypes were identified that are substantially enriched (1,000fold) in the CD137+ population compared to the CD137− population (FIG. 7panel A). The frequency of these clonotypes in the unsorted sampleranged from as high as 0.81% to as low as 0.004% (FIG. 7 panel B). Theseclonotypes were enriched in the CD137+ population compared to theunsorted PBMC sample by ˜100 fold. To ensure that these cells wereactivated due to stimulation with the peptide, a control experiment wasperformed with no peptide. None of the 9 clonotypes that were enrichedwith the peptide in the CD137+ population enriched following incubationwithout peptide in CD137+ cells (FIG. 7 panel C).

Specific clonotypes identified by the pentamer and CD137 assays werecompared and found to substantially overlap. All 8 clonotypes that wereidentified with the pentamer assay were also identified by CD137 assay(FIG. 8 panel A), although an additional clonotype was identified by theCD137 assay that was not identified in the pentamer assay.

A third functional assay for identification of antigen-specificclonotypes was conducted by combining capture of proliferating cellsfollowing incubation with pp65₄₉₅ peptide and repertoire sequencing.Cells were labeled with CFSE and incubated with either pp65₄₉₅ or nopeptide for 6 days. Proliferating CD8 cells were then sorted based ondilution of CFSE. pp65₄₉₅-specific clonotypes were identified based ontheir relative frequency in the CFSE^(low) population compared to thatof fresh unsorted PBMCs.

Sixteen clonotypes were identified that were substantially increased inthe CFSE^(low) population, and the frequency of some of the identifiedclonotypes was below 10^(±5) (FIG. 9 panel A). An identicalproliferation assay was used that lacked the peptide as a control. Noneof the 16 clonotypes identified by the proliferation assay were enrichedin the CFSE^(low) population when no peptide was used (FIG. 9 panel B).

One advantage to using indirect immune monitoring assays compared topentamer reagents is the ability to assess responses to more than onepeptide antigen at the same time. A pool of 138 peptides spanning theentire pp65 protein (herein referred to as pp65pool) was used tostimulate PBMCs in the proliferation assay to identify pp65pool-specificT cells. Repertoire analysis of proliferating cells following pp65poolincubation enabled identification of 25 clonotypes. Of these 25clonotypes identified using the pp65pool, 12 of these were also deemedantigen-specific with the single pp65₄₉₅ peptide, demonstrating therepeatability of the approach.

Seven of eight clonotypes identified by the pentamer assay wereidentified in the pp65pool proliferation assay, demonstrating that theuse of peptide pool does not substantially decrease sensitivity. Inaddition the proliferation assay with the pp65pool enabledidentification of additional clonotypes that are presumably specific toother peptides within the pool. Most of the additional clonotypesidentified with the pp65pool were not enriched in the pentamer+population (FIG. 9 panel D) consistent with them being not specific tothe pp65₄₉₅ peptide.

While the present invention has been described with reference to severalparticular example embodiments, those skilled in the art will recognizethat many changes may be made thereto without departing from the spiritand scope of the present invention. The present invention is applicableto a variety of sensor implementations and other subject matter, inaddition to those discussed above.

DEFINITIONS

Unless otherwise specifically defined herein, terms and symbols ofnucleic acid chemistry, biochemistry, genetics, and molecular biologyused herein follow those of standard treatises and texts in the field,e.g. Kornberg and Baker, DNA Replication. Second Edition (W.H. Freeman.New York, 1992); Lehninger, Biochemistry. Second Edition (WorthPublishers, New York, 1975); Strachan and Read. Human MolecularGenetics, Second Edition (Wiley-Liss, New York, 1999); Abbas et al,Cellular and Molecular Immunology, 6^(th) edition (Saunders, 2007).

“Activation” or “immune activation” or “activated”, especially inreference to T-cells, means a phase of an adaptive immune response thatfollows the antigen recognition phase (during which antigen-specificlymphocytes bind to antigens) and is characterized by proliferation oflymphocytes and their differentiation into effector cells. e.g. Abbas etal. Cellular and Molecular Immunology, Fourth Edition, (W.B. SaundersCompany, 2000). Activation of T cells may be associated with secretionof certain cytokines that are detectable using conventional assays, suchas an ELISPOT assay, and may be associated with the expression ofcharacteristic cell surface markers, such as CD25, CD134, CD69, CD137.CD154, or the like, e.g. Gratama et al, Cytometry A, 73A: 971-974(2008).

“Aligning” means a method of comparing a test sequence, such as asequence read, to one or more reference sequences to determine whichreference sequence or which portion of a reference sequence is closestbased on some sequence distance measure. An exemplary method of aligningnucleotide sequences is the Smith Waterman algorithm. Distance measuresmay include Hamming distance, Levenshtein distance, or the like.Distance measures may include a component related to the quality valuesof nucleotides of the sequences being compared.

“Amplicon” means the product of a polynucleotide amplification reaction;that is, a clonal population of polynucleotides, which may be singlestranded or double stranded, which are replicated from one or morestarting sequences. The one or more starting sequences may be one ormore copies of the same sequence, or they may be a mixture of differentsequences. Preferably, amplicons are formed by the amplification of asingle starting sequence. Amplicons may be produced by a variety ofamplification reactions whose products comprise replicates of the one ormore starting, or target, nucleic acids. In one aspect, amplificationreactions producing amplicons are “template-driven” in that base pairingof reactants, either nucleotides or oligonucleotides, have complementsin a template polynucleotide that are required for the creation ofreaction products. In one aspect, template-driven reactions are primerextensions with a nucleic acid polymerase or oligonucleotide ligationswith a nucleic acid ligase. Such reactions include, but are not limitedto, polymerase chain reactions (PCRs), linear polymerase reactions,nucleic acid sequence-based amplification (NASBAs), rolling circleamplifications, and the like, disclosed in the following references thatare incorporated herein by reference: Mullis et al, U.S. Pat. Nos.4,683,195; 4,965,188; 4,683,202; 4,800,159 (PCR); Gelfand et al, U.S.Pat. No. 5,210,015 (real-time PCR with “taqman” probes); Wittwer et al,U.S. Pat. No. 6,174,670; Kacian et al. U.S. Pat. No. 5,399,491(“NASBA”); Lizardi. U.S. Pat. No. 5,854,033; Aono et al. Japanese patentpubl. JP 4-262799 (rolling circle amplification); and the like. In oneaspect, amplicons of the invention are produced by PCRs. Anamplification reaction may be a “real-time” amplification if a detectionchemistry is available that permits a reaction product to be measured asthe amplification reaction progresses, e.g. “real-time PCR” describedbelow, or “real-time NASBA” as described in Leone et al, Nucleic AcidsResearch, 26: 2150-2155 (1998), and like references. As used herein, theterm “amplifying” means performing an amplification reaction. A“reaction mixture” means a solution containing all the necessaryreactants for performing a reaction, which may include, but not belimited to, buffering agents to maintain pH at a selected level during areaction, salts, co-factors, scavengers, and the like.

“Clonotype” means a recombined nucleotide sequence of a lymphocyte whichencodes an immune receptor or a portion thereof. More particularly,clonotype means a recombined nucleotide sequence of a T cell or B cellwhich encodes a T cell receptor (TCR) or B cell receptor (BCR), or aportion thereof. In various embodiments, clonotypes may encode all or aportion of a VDJ rearrangement of IgH, a DJ rearrangement of IgH, a VJrearrangement of IgK, a VJ rearrangement of igL, a VDJ rearrangement ofTCR β, a DJ rearrangement of TCR β, a VJ rearrangement of TCR α, a VJrearrangement of TCR γ, a VDJ rearrangement of TCR δ, a VD rearrangementof TCR δ, a Kde-V rearrangement, or the like. Clonotypes may also encodetranslocation breakpoint regions involving immune receptor genes, suchas BclI-IgH or Bcl-IgH. In one aspect, clonotypes have sequences thatare sufficiently long to represent or reflect the diversity of theimmune molecules that they are derived from; consequently, clonotypesmay vary widely in length. In some embodiments, clonotypes have lengthsin the range of from 25 to 400 nucleotides; in other embodiments,clonotypes have lengths in the range of from 25 to 200 nucleotides.

“Clonotype profile” means a listing of distinct clonotypes and theirrelative abundances that are derived from a population of lymphocytes.Typically, the population of lymphocytes are obtained from a tissuesample. The term “clonotype profile” is related to, but more generalthan, the immunology concept of immune “repertoire” as described inreferences, such as the following: Arstila et al. Science, 2116: 958-961(1999); Yassai et al. Immunogenetics, 61: 493-502 (2009); Kedzierska etal, Mol. Immunol., 45(3): 607-618 (2008); and the like. The term“clonotype profile” includes a wide variety of lists and abundances ofrearranged immune receptor-encoding nucleic acids, which may be derivedfrom selected subsets of lymphocytes (e.g. tissue-infiltratinglymphocytes, immunophenotypic subsets, or the like), or which may encodeportions of immune receptors that have reduced diversity as compared tofull immune receptors. In some embodiments, clonotype profiles maycomprise at least 10³ distinct clonotypes; in other embodiments,clonotype profiles may comprise at least 10⁴ distinct clonotypes; inother embodiments, clonotype profiles may comprise at least 10⁵ distinctclonotypes; in other embodiments, clonotype profiles may comprise atleast 10⁶ distinct clonotypes. In such embodiments, such clonotypeprofiles may further comprise abundances or relative frequencies of eachof the distinct clonotypes. In one aspect, a clonotype profile is a setof distinct recombined nucleotide sequences (with their abundances) thatencode T cell receptors (TCRs) or B cell receptors (BCRs), or fragmentsthereof, respectively, in a population of lymphocytes of an individual,wherein the nucleotide sequences of the set have a one-to-onecorrespondence with distinct lymphocytes or their clonal subpopulationsfor substantially all of the lymphocytes of the population. In oneaspect, nucleic acid segments defining clonotypes are selected so thattheir diversity (i.e. the number of distinct nucleic acid sequences inthe set) is large enough so that substantially every T cell or B cell orclone thereof in an individual carries a unique nucleic acid sequence ofsuch repertoire. That is, preferably each different clone of a samplehas different clonotype. In other aspects of the invention, thepopulation of lymphocytes corresponding to a repertoire may becirculating B cells, or may be circulating T cells, or may besubpopulations of either of the foregoing populations, including but notlimited to, CD4+ T cells, or CD8+ T cells, or other subpopulationsdefined by cell surface markers, or the like. Such subpopulations may beacquired by taking samples from particular tissues, e.g. bone marrow, orlymph nodes, or the like, or by sorting or enriching cells from a sample(such as peripheral blood) based on one or more cell surface markers,size, morphology, or the like. In still other aspects, the population oflymphocytes corresponding to a repertoire may be derived from diseasetissues, such as a tumor tissue, an infected tissue, or the like. In oneembodiment, a clonotype profile comprising human TCR β chains orfragments thereof comprises a number of distinct nucleotide sequences inthe range of from 0.1×10⁶ to 1.8×10⁶, or in the range of from 0.5×10⁶ to1.5×10⁶ or in the range of from 0.8×10⁶ to 1.2×10⁶. In anotherembodiment, a clonotype profile comprising human IgH chains or fragmentsthereof comprises a number of distinct nucleotide sequences in the rangeof from 0.1×10⁶ to 1.8×10⁶, or in the range of from 0.5×10⁶ to 1.5×10⁶,or in the range of from 0.8×10⁶ to 1.2×10⁶. In a particular embodiment,a clonotype profile of the invention comprises a set of nucleotidesequences encoding substantially all segments of the V(D)J region of anIgH chain. In one aspect, “substantially all” as used herein means everysegment having a relative abundance of 0.001 percent or higher; or inanother aspect. “substantially all” as used herein means every segmenthaving a relative abundance of 0.0001 percent or higher. In anotherparticular embodiment, a clonotype profile of the invention comprises aset of nucleotide sequences that encodes substantially all segments ofthe V(D)J region of a TCR β chain. In another embodiment, a clonotypeprofile of the invention comprises a set of nucleotide sequences havinglengths in the range of from 25-200 nucleotides and including segmentsof the V. D, and J regions of a TCR β chain. In another embodiment, aclonotype profile of the invention comprises a set of nucleotidesequences having lengths in the range of from 25-200 nucleotides andincluding segments of the V, D, and J regions of an IgH chain. Inanother embodiment, a clonotype profile of the invention comprises anumber of distinct nucleotide sequences that is substantially equivalentto the number of lymphocytes expressing a distinct IgH chain. In anotherembodiment, a clonotype profile of the invention comprises a number ofdistinct nucleotide sequences that is substantially equivalent to thenumber of lymphocytes expressing a distinct TCR β chain. In stillanother embodiment, “substantially equivalent” means that withninety-nine percent probability a clonotype profile will include anucleotide sequence encoding an IgH or TCR β or portion thereof carriedor expressed by every lymphocyte of a population of an individual at afrequency of 0.001 percent or greater. In still another embodiment,“substantially equivalent” means that with ninety-nine percentprobability a repertoire of nucleotide sequences will include anucleotide sequence encoding an IgH or TCR β or portion thereof carriedor expressed by every lymphocyte present at a frequency of 0.0001percent or greater. In some embodiments, clonotype profiles are derivedfrom samples comprising from 10³ to 10⁷ lymphocytes. Such numbers oflymphocytes may be obtained from peripheral blood samples of from 1-10mL.

“Coalescing” means treating two candidate clonotypes with sequencedifferences as the same by determining that such differences are due toexperimental or measurement error and not due to genuine biologicaldifferences. In one aspect, a sequence of a higher frequency candidateclonotype is compared to that of a lower frequency candidate clonotypeand if predetermined criteria are satisfied then the number of lowerfrequency candidate clonotypes is added to that of the higher frequencycandidate clonotype and the lower frequency candidate clonotype isthereafter disregarded. That is, the read counts associated with thelower frequency candidate clonotype are added to those of the higherfrequency candidate clonotype.

“Complementarity determining regions” (CDRs) mean regions of animmunoglobulin (i.e., antibody) or T cell receptor where the moleculecomplements an antigen's conformation, thereby determining themolecule's specificity and contact with a specific antigen. T cellreceptors and immunoglobulins each have three CDRs: CDR1 and CDR2 arefound in the variable (V) domain, and CDR3 includes some of V, all ofdiverse (D) (heavy chains only) and joint (J), and some of the constant(C) domains.

“Data structure” means an organization of information, usually in acomputer or memory device, for better algorithm efficiency. Exemplarydata structures include queues, stacks, linked lists, heaps, hashtables, arrays, trees, and the like. Data structures may havesubstructures that correspond to units of information or to subsets ofrelated information. For example, arrays have rows and columns ofentries: trees have nodes, branches, subtrees, and leaves; or the like.In one aspect, a data structure used herein is a sequence tree, an arrayor a hash table.

“Microfluidics device” means an integrated system of one or morechambers, ports, and channels that are interconnected and in fluidcommunication and designed for carrying out an analytical reaction orprocess, either alone or in cooperation with an appliance or instrumentthat provides support functions, such as sample introduction, fluidand/or reagent driving means, temperature control, detection systems,data collection and/or integration systems, and the like. Microfluidicsdevices may further include valves, pumps, and specialized functionalcoatings on interior walls, e.g. to prevent adsorption of samplecomponents or reactants, facilitate reagent movement by electroosmosis,or the like. Such devices are usually fabricated in or as a solidsubstrate, which may be glass, plastic, or other solid polymericmaterials, and typically have a planar format for ease of detecting andmonitoring sample and reagent movement, especially via optical orelectrochemical methods. Features of a microfluidic device usually havecross-sectional dimensions of less than a few hundred square micrometersand passages typically have capillary dimensions, e.g. having maximalcross-sectional dimensions of from about 500 μm to about 0.1 μm.Microfluidics devices typically have volume capacities in the range offrom 1 μL to a few nL, e.g. 10-100 nL. The fabrication and operation ofmicrofluidics devices are well-known in the art as exemplified by thefollowing references that are incorporated by reference: Ramsey, U.S.Pat. Nos. 6,001,229; 5,858,195; 6,010,607; and 6,033,546; Soane et al.U.S. Pat. Nos. 5,126,022 and 6,054,034; Nelson et al, U.S. Pat. No.6,613,525; Maher et at U.S. Pat. No. 6,399,952; Ricco et al.International patent publication WO 02/24322; Bjornson et al,International patent publication WO 99/19717; Wilding et al, U.S. Pat.Nos. 5,587,128; 5,498,392; Sia et al, Electrophoresis, 24: 3563-3576(2003

“Percent homologous,” “percent identical.” or like terms used inreference to the comparison of a reference sequence and another sequence(“comparison sequence”) mean that in an optimal alignment between thetwo sequences, the comparison sequence is identical to the referencesequence in a number of subunit positions equivalent to the indicatedpercentage, the subunits being nucleotides for polynucleotidecomparisons or amino acids for polypeptide comparisons. As used herein,an “optimal alignment” of sequences being compared is one that maximizesmatches between subunits and minimizes the number of gaps employed inconstructing an alignment. Percent identities may be determined withcommercially available implementations of algorithms, such as thatdescribed by Needleman and Wunsch. J. Mol. Biol., 48: 443-453(1970)(“GAP” program of Wisconsin Sequence Analysis Package. GeneticsComputer Group, Madison, Wis.), or the like. Other software packages inthe art for constructing alignments and calculating percentage identityor other measures of similarity include the “BestFit” program, based onthe algorithm of Smith and Waterman, Advances in Applied Mathematics, 2:482-489 (1981) (Wisconsin Sequence Analysis Package. Genetics ComputerGroup, Madison, Wis.). In other words, for example, to obtain apolynucleotide having a nucleotide sequence at least 95 percentidentical to a reference nucleotide sequence, up to five percent of thenucleotides in the reference sequence may be deleted or substituted withanother nucleotide, or a number of nucleotides up to five percent of thetotal number of nucleotides in the reference sequence may be insertedinto the reference sequence.

“Polymerase chain reaction,” or “PCR.” means a reaction for the in vitroamplification of specific DNA sequences by the simultaneous primerextension of complementary strands of DNA. In other words, PCR is areaction for making multiple copies or replicates of a target nucleicacid flanked by primer binding sites, such reaction comprising one ormore repetitions of the following steps: (i) denaturing the targetnucleic acid, (ii) annealing primers to the primer binding sites, and(iii) extending the primers by a nucleic acid polymerase in the presenceof nucleoside triphosphates. Usually, the reaction is cycled throughdifferent temperatures optimized for each step in a thermal cyclerinstrument. Particular temperatures, durations at each step, and ratesof change between steps depend on many factors well-known to those ofordinary skill in the art, e.g. exemplified by the references: McPhersonet al, editors. PCR: A Practical Approach and PCR2: A Practical Approach(IRL Press, Oxford, 1991 and 1995, respectively). For example, in aconventional PCR using Taq DNA polymerase, a double stranded targetnucleic acid may be denatured at a temperature >90° C. primers annealedat a temperature in the range 50-75° C., and primers extended at atemperature in the range 72-78° C. The term “PCR” encompasses derivativeforms of the reaction, including but not limited to, RT-PCR, real-limePCR, nested PCR quantitative PCR, multiplexed PCR, and the like.Reaction volumes range from a few hundred nanoliters, e.g. 200 nL, to afew hundred μL. e.g. 200 μL. “Reverse transcription PCR,” or “RT-PCR,”means a PCR that is preceded by a reverse transcription reaction thatconverts a target RNA to a complementary single stranded DNA, which isthen amplified, e.g. Tecott et al. U.S. Pat. No. 5,168,038, which patentis incorporated herein by reference. “Real-time PCR” means a PCR forwhich the amount of reaction product. i.e. amplicon, is monitored as thereaction proceeds. There are many forms of real-time PCR that differmainly in the detection chemistries used for monitoring the reactionproduct, e.g. Gelfand et al, U.S. Pat. No. 5,210,015 (“taqman”); Wittweret al, U.S. Pat. Nos. 6,174,670 and 6,569,627 (intercalating dyes);Tyagi et al. U.S. Pat. No. 5,925,517 (molecular beacons); which patentsare incorporated herein by reference. Detection chemistries forreal-time PCR are reviewed in Mackay et al. Nucleic Acids Research, 30:1292-1305 (2002), which is also incorporated herein by reference.“Nested PCR” means a two-stage PCR wherein the amplicon of a first PCRbecomes the sample for a second PCR using a new set of primers, at leastone of which binds to an interior location of the first amplicon. Asused herein, “initial primers” in reference to a nested amplificationreaction mean the primers used to generate a first amplicon, and“secondary primers” mean the one or more primers used to generate asecond, or nested, amplicon. “Multiplexed PCR” means a PCR whereinmultiple target sequences (or a single target sequence and one or morereference sequences) are simultaneously carried out in the same reactionmixture. e.g. Bernard et al. Anal. Biochem., 273: 221-228(1999)(two-color real-time PCR). Usually, distinct sets of primers areemployed for each sequence being amplified. Typically, the number oftarget sequences in a multiplex PCR is in the range of from 2 to 50, orfrom 2 to 40, or from 2 to 30. “Quantitative PCR” means a PCR designedto measure the abundance of one or more specific target sequences in asample or specimen. Quantitative PCR includes both absolute quantitationand relative quantitation of such target sequences. Quantitativemeasurements are made using one or more reference sequences or internalstandards that may be assayed separately or together with a targetsequence. The reference sequence may be endogenous or exogenous to asample or specimen, and in the latter case, may comprise one or morecompetitor templates. Typical endogenous reference sequences includesegments of transcripts of the following genes: β-actin, GAPDH,β₂-microglobulin, ribosomal RNA, and the like. Techniques forquantitative PCR are well-known to those of ordinary skill in the art,as exemplified in the following references that are incorporated byreference: Freeman et al, Biotechniques, 26: 112-126 (1999);Becker-Andre et al. Nucleic Acids Research, 17: 9437-9447 (1989);Zimmerman et al, Biotechniques, 21: 268-279 (1996); Diviacco et al.Gene, 122: 3013-3020 (1992); Becker-Andre et al. Nucleic Acids Research,17: 9437-9446 (1989); and the like.

“Polymerase cycling assembly” or “PCA” reaction (also referred to hereinas “linked PCR”) means a PCR that comprises at least one pair of outerprimers and at least one pair of inner primers. An inner primer has a 3′portion that is complementary to a target nucleic acid (or itscomplement) and a 5′ portion that is complementary to the 5′ portion ofanother inner primer corresponding to a different target nucleic acid.

“Primer” means an oligonucleotide, either natural or synthetic that iscapable, upon forming a duplex with a polynucleotide template, of actingas a point of initiation of nucleic acid synthesis and being extendedfrom its 3′ end along the template so that an extended duplex is formed.Extension of a primer is usually carried out with a nucleic acidpolymerase, such as a DNA or RNA polymerase. The sequence of nucleotidesadded in the extension process is determined by the sequence of thetemplate polynucleotide. Usually primers are extended by a DNApolymerase. Primers usually have a length in the range of from 14 to 40nucleotides, or in the range of from 18 to 36 nucleotides. Primers areemployed in a variety of nucleic amplification reactions, for example,linear amplification reactions using a single primer, or polymerasechain reactions, employing two or more primers. Guidance for selectingthe lengths and sequences of primers for particular applications is wellknown to those of ordinary skill in the art, as evidenced by thefollowing references that are incorporated by reference: Dieffenbach,editor, PCR Primer A Laboratory Manual, 2^(nd) Edition (Cold SpringHarbor Press, New York, 2003).

“Quality score” means a measure of the probability that a baseassignment at a particular sequence location is correct. A varietymethods are well known to those of ordinary skill for calculatingquality scores for particular circumstances, such as, for bases calledas a result of different sequencing chemistries, detection systems,base-calling algorithms, and so on. Generally, quality score values aremonotonically related to probabilities of correct base calling. Forexample, a quality score, or Q, of 10 may mean that there is a 90percent chance that a base is called correctly, a Q of 20 may mean thatthere is a 99 percent chance that a base is called correctly, and so on.For some sequencing platforms, particularly those usingsequencing-by-synthesis chemistries, average quality scores decrease asa function of sequence read length, so that quality scores at thebeginning of a sequence read are higher than those at the end of asequence read, such declines being due to phenomena such as incompleteextensions, carry forward extensions, loss of template, loss ofpolymerase, capping failures, deprotection failures, and the like.

“Sequence read” means a sequence of nucleotides determined from asequence or stream of data generated by a sequencing technique, whichdetermination is made, for example, by means of base-calling softwareassociated with the technique, e.g. base-calling software from acommercial provider of a DNA sequencing platform. A sequence readusually includes quality scores for each nucleotide in the sequence.Typically, sequence reads are made by extending a primer along atemplate nucleic acid. e.g. with a DNA polymerase or a DNA ligase. Datais generated by recording signals, such as optical, chemical (e.g. pHchange), or electrical signals, associated with such extension. Suchinitial data is converted into a sequence read.

“Sequence tag” (or “tag”) or “barcode” means an oligonucleotide that isattached, usually via a covalent bond, to another molecule or molecularcomplex and that is used to identify and/or track the other molecule ina reaction or a series of reactions. Sequence tags may vary widely insize and compositions; the following references, which are incorporatedherein by reference, provide guidance for selecting sets of sequencetags appropriate for particular embodiments: Brenner, U.S. Pat. No.5,635,400; Brenner and Macevicz, U.S. Pat. No. 7,537,897; Brenner et al,Proc. Natl. Acad. Sci., 97: 1665-1670 (2000); Church et al, Europeanpatent publication 0 303 459; Shoemaker et al, Nature Genetics, 14:450-40-456 (1996); Morris et al, European patent publication 0799897A1;Wallace, U.S. Pat. No. 5,981,179; and the like. Lengths and compositionsof sequence tags can vary widely, and the selection of particularlengths and/or compositions depends on several factors including,without limitation, how tags are used to generate a readout. e.g. via ahybridization reaction or via an enzymatic reaction, such asamplification and sequencing; whether they are labeled, e.g. with afluorescent dye or the like; the number of distinguishable sequence tagsrequired to unambiguously identify a set of molecules of interest, andthe like, and how different must tags of a set be in order to ensurereliable identification, e.g. freedom from cross hybridization,misidentification from sequencing errors, or the like. In someembodiments, sequence tags may each have a length within a range of from6 to 36 nucleotides, or from 4 to 30 nucleotides, or from 8 to 40nucleotides, or from 6 to 50 nucleotides, respectively; provided,however, that the term “sequence tag” may also be used in reference to asequence tag of the foregoing lengths sandwiched between a pair ofprimers that may be used to amplify or otherwise manipulate the sequencetag, for example, in order to identify it by DNA sequencing. In oneaspect, sets of sequence tags are used wherein each sequence tag of aset has a unique nucleotide sequence that differs from that of everyother tag of the same set by a plurality of bases; in some embodiments,such plurality is at least three bases; in another aspect, sets ofsequence tags are used wherein the sequence of each tag of a set differsfront that of every other tag of the same set by at least four bases.

“Sequence tree” means a tree data structure for representing nucleotidesequences. In one aspect, a tree data structure of the invention is arooted directed tree comprising nodes and edges that do not includecycles, or cyclical pathways. Edges from nodes of tree data structuresof the invention are usually ordered. Nodes and/or edges are structuresthat may contain, or be associated with, a value. Each node in a treehas zero or more child nodes, which by convention are shown below it inthe tree. A node that has a child is called the child's parent node. Anode has at most one parent. Nodes that do not have any children arecalled leaf nodes. The topmost node in a tree is called the root node.Being the topmost node, the root node will not have parents. It is thenode at which operations on the tree commonly begin (although somealgorithms begin with the leaf nodes and work up ending at the root).All other nodes can be reached from it by following edges or links.

What is claimed is:
 1. A method of determining antigen-specific T cellsin a tissue sample, comprising the steps of: exposing a tissue sample toan antigen in a reaction mixture; enriching T cells from the reactionmixture that interact with the antigen into a subset; sequencingrecombined nucleic acids encoding a T-cell receptor chain or a portionthereof from a sample of enriched T cells to provide sequence reads fromwhich clonotypes are determined; sequencing recombined nucleic acidsencoding a T-cell receptor chain or a portion thereof from the tissuesample of from T cells that do not interact with the antigen to providesequence reads from which clonotypes are determined; and determiningantigen-specific T cells in the tissue sample as T cells whose clonotypefrequencies increase in the subset of enriched T cells relative to thefrequencies of the same clonotypes in the tissue sample or in the Tcells that do not interact with the antigen.
 2. The method of claim 1wherein said step of exposing includes incubating said antigen with saidtissue sample for at least a predetermined interval.
 3. The method ofclaim 2 wherein said antigen is a protein or a plurality of peptidesderived from a protein.
 4. The method of claim 1 wherein said step ofsequencing includes isolating individual molecules of said recombinednucleic acids on a solid surface and sequencing the isolated individualmolecules or clones thereof to provide said sequence reads.
 5. Themethod of claim 4 wherein said method further includes a step ofcoalescing a plurality of said sequence reads to determine each of saidclonotypes.
 6. The method of claim 1 wherein said step of enrichingincludes sorting said T cells from said reaction mixture that interactwith said antigen.
 7. The method of claim 6 wherein said step of sortingis implemented with an antigen reagent capable of forming a complex witha T cell specific for said antigen or wherein said step of sorting isimplemented with a binding compound specific for an activation marker.8. The method of claim 7 wherein said antigen reagent is a peptide-MHCmultimer complex wherein the peptide of the complex is derived from saidantigen.
 9. The method of claim 1 wherein said tissue sample comprisestissue samples from a plurality of individuals.
 10. The method of claim1 wherein said tissue sample comprises peripheral blood or is derivedfrom peripheral blood.
 11. A method of determining receptors ofantigen-specific T cells in a tissue sample, the method comprising thesteps of: forming a plurality of subsets from a tissue sample containingT cells; exposing under interaction conditions the T cells of eachsubset to an antigen; isolating the antigen-interacting T cells of eachsubset; sequencing recombined nucleic acids encoding T-cell receptor αchains in each subset to provide sequence reads from which α chainclonotypes are determined; sequencing recombined nucleic acids encodingT-cell receptor β chains in each subset to provide sequence reads fromwhich β chain clonotypes are determined; identifying as antigen-specificT cell receptors with those pairs of α chain clonotypes and β chainclonotypes that for every subset either (i) both α chain and β chainclonotypes are present in a subset or neither α chain nor β chainclonotypes are present in a subset, and (iii) both the α chain and βchain clonotypes are present in at least one subset and the α chain andβ chain clonotypes are not present in at least one subset.
 12. Themethod of claim 11 wherein said tissue sample contains a population ofsaid T cells, the population having a size and each different T cell ofthe population having a frequency within the population, and whereinsaid plurality of said subsets depends on said size of the populationand the frequency of said T cells whose T-cell receptor α chains andT-cell receptor β chains are to be determined.
 13. The method of claim11 wherein a size of said tissue sample and said plurality of subsetsare selected so that said T cells of said sample are distributed amongsaid subsets in accordance with a binomial model.
 14. The method ofclaim 11 wherein said step of reacting includes incubating said antigenwith said tissue sample for at least a predetermined interval.
 15. Themethod of claim 11 wherein said antigen is a protein or a plurality ofpeptides derived from a protein.
 16. The method of claim 11 wherein saidstep of isolating is implemented with an antigen reagent or with abinding compound specific for an activation marker.
 17. The method ofclaim 11 wherein said tissue sample comprises tissue samples from aplurality of individuals.
 18. The method of claim 11 wherein said tissuesample comprises peripheral blood or is derived from peripheral blood.19. A method of determining clonotypes of antigen-specific T cells in atissue sample, the method comprising the steps of: (a) forming aplurality of subsets from a tissue sample containing T cells; (b)exposing under interaction conditions T cells in a subplurality ofsubsets to one or more antigens so that T cells specific for any of theone or more antigens are capable of interacting therewith, wherein eachdifferent antigen is exposed to T cells in a different subplurality; (c)enriching the antigen-interacting T cells of each subset of asubplurality; (d) sequencing recombined nucleic acids encoding a T-cellreceptor chain or a portion thereof from said enriched T cells in eachsubset of the subplurality to provide sequence reads from whichclonotypes are determined; (e) sequencing recombined nucleic acidsencoding T-cell receptor chain or a portion thereof from said T cells ineach subset of the subplurality prior to said step of enriching or fromnon-enriched T cells in each subset of the subplurality to providesequence reads from which clonotypes are determined; and (f) identifyinga clonotype of a T cell specific for an antigen of the one or moreantigens as a clonotype whose frequency increases in substantially everysubset of a subplurality corresponding to the antigen and does notincrease in substantially every other subset.
 20. The method of claim 19wherein said tissue sample contains a population of said T cells, thepopulation having a size and each different T cell of the populationhaving a frequency within the population, and wherein said plurality ofsaid subsets depends on said size of the population and the frequency ofsaid T cells whose clonotypes are to be determined.
 21. The method ofclaim 19 wherein said step of exposing includes reacting underactivation conditions said antigens with said T cells.
 22. The method ofclaim 21 wherein said step of reacting further includes incubating saidantigens with said T cells for at least a predetermined interval. 23.The method of claim 19 wherein said antigen is a protein or a pluralityof peptides derived from a protein and wherein said tissue samplecomprises peripheral blood or is derived from peripheral blood.
 24. Themethod of claim 19 wherein said step of isolating is implemented with anantigen reagent with a binding compound specific for an activationmarker.